{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 50]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 18]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 35", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 35]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 46", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 46]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 50]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 18]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 15", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 15]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 27]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 12", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 12]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 48]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 22]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 40", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 40]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 27]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 35", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 35]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 20", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 20]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 36]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 17", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 17]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 42]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 45", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 45]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 20", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 20]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 22]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 19", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 19]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 21", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 21]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 28", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 28]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 50]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 42]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 42]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 33", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 33]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 42]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 34]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 30", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 30]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 24", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 24]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 17", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 17]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 48]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 24", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 24]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 26", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 26]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 27]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 33", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 33]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 36]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 35", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 35]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 31", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 31]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 15", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 15]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 22]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 25", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 25]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 18]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 38", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 38]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 42]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 20", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 20]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 50]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 21", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 21]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 43", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 43]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 40", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 40]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 49", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 49]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 26", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 26]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 39", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 39]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 18]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 16", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 16]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 10", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 10]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 17", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 17]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 15", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 15]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 50]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 36]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 46", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 46]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 21", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 21]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 27]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 22]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 49", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 49]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 29", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 29]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 41", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 41]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 16", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 16]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 20", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 20]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 42]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 23", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 23]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 27]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 49", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 49]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 45", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 45]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 49", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 49]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 13", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 13]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 11", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 11]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 18]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 38", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 38]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 35", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 35]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 32]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 46", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 46]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 36]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 31", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 31]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 27]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 23", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 23]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 32]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 29", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 29]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 11", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 11]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 48]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 31", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 31]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 18]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 50]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 29", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 29]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 44", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 44]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 17", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 17]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 17", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 17]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 12", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 12]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 48]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 19", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 19]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 41", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 41]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 23", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 23]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 11", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 11]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 48]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 42]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 26", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 26]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 34]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 32]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 13", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 13]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 15", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 15]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 34]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 45", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 45]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 24", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 24]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 30", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 30]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 10", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 10]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 46", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 46]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 35", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 35]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 47", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 47]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 36]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 32]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 38", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 38]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 36]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 48]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 10", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 10]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 29", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 29]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 20", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 20]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 22]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 48]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 16", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 16]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 21", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 21]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 32]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 48]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 22]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 14", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 14]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 36]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 18]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 34]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 25", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 25]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 34]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 14", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 14]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 43", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 43]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 43", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 43]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 34]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 24", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 24]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 34]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 45", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 45]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 43", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 43]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 30", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 30]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 31", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 31]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 44", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 44]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 43", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 43]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 15", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 15]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 13", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 13]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 18]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 48]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 48]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 25", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 25]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 37", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 37]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 12", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 12]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 45", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 45]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 38", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 38]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 25", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 25]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 25", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 25]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 24", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 24]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 34]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 22]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 13", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 13]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 46", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 46]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 46", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 46]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 27]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 11", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 11]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 44", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 44]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 32]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 33", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 33]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 37", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 37]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 33", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 33]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 37", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 37]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 29", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 29]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 46", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 46]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 44", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 44]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 38", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 38]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 23", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 23]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 24", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 24]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 12", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 12]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 48]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 40", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 40]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 17", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 17]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 37", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 37]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 32]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 46", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 46]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 24", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 24]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 27]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 20", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 20]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 31", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 31]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 14", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 14]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 23", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 23]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 30", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 30]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 11", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 11]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 50]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 32]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 31", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 31]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 21", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 21]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 44", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 44]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 18]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 38", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 38]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 34]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 46", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 46]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 34]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 47", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 47]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 29", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 29]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 25", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 25]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 12", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 12]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 39", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 39]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 37", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 37]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 47", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 47]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 22]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 14", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 14]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 48", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 48]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 47", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 47]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 34]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 47", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 47]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 27]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 20", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 20]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 42]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 32]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 36]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 22]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 43", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 43]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 22", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 22]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 19", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 19]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 50]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 20", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 20]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 30", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 30]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 42]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 27]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 10", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 10]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 50]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 11", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 11]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 47", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 47]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 41", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 41]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 28", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 28]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 15", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 15]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 39", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 39]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 37", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 37]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 27]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 12", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 12]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 39", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 39]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 35", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 35]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 40", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 40]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 36]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 47", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 47]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 41", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 41]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 32]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 21", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 21]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 11", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 11]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average price grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 42]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 42]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 33", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 33]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 32]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 38", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 38]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 30", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 30]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 16", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 16]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 37", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 37]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 11", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 11]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where quantity is greater than 29", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['quantity'] > 29]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 38", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 38]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 47", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 47]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 18", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 18]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 49", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 49]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 27]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 33", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 33]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 40", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 40]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 31", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 31]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 35", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 35]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and compute the average salary grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 47", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 47]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 30", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 30]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 36", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 36]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 16", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 16]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 27", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 27]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 29", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 29]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 42", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 42]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and compute the average price grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['price'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['age'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average score grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['score'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 10", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 10]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 34", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 34]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where price is greater than 50", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 50]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average quantity grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['quantity'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where age is greater than 40", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 40]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and compute the average salary grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['salary'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 19", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 19]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 31", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 31]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['score'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Read a CSV file and compute the average quantity grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['quantity'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 15", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 15]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average age grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['age'].mean()\nprint(result)"}
{"instruction": "Read a CSV file and calculate the mean of the age column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['age'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 24", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 24]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and compute the average quantity grouped by department", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('department')['quantity'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the score column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['score'] = np.where(df['score'] < 0, 0, df['score'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where score is greater than 24", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 24]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average price grouped by category", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('category')['price'].mean()\nprint(result)"}
{"instruction": "Replace negative values with zero in the salary column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['salary'] = np.where(df['salary'] < 0, 0, df['salary'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Using numpy, calculate the mean of values in the price column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['price'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 26", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 26]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the score column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['score'].mean())"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Replace negative values with zero in the age column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['age'] = np.where(df['age'] < 0, 0, df['age'])\nprint(df)"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where salary is greater than 28", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['salary'] > 28]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where score is greater than 29", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 29]\nprint(filtered_df)"}
{"instruction": "Load a CSV file and filter rows where price is greater than 38", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 38]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the quantity column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['quantity'] = np.where(df['quantity'] < 0, 0, df['quantity'])\nprint(df)"}
{"instruction": "Read a CSV file and calculate the mean of the salary column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['salary'].mean())"}
{"instruction": "Load a CSV file and filter rows where price is greater than 32", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['price'] > 32]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Load a CSV file and filter rows where score is greater than 40", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['score'] > 40]\nprint(filtered_df)"}
{"instruction": "Using numpy, calculate the mean of values in the score column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['score'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Read a CSV file and calculate the mean of the quantity column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['quantity'].mean())"}
{"instruction": "Read a CSV file and compute the average score grouped by region", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nresult = df.groupby('region')['score'].mean()\nprint(result)"}
{"instruction": "Using numpy, calculate the mean of values in the age column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['age'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Load a CSV file and filter rows where age is greater than 39", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 39]\nprint(filtered_df)"}
{"instruction": "Read a CSV file and calculate the mean of the price column", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nprint(df['price'].mean())"}
{"instruction": "Load a CSV file and filter rows where age is greater than 12", "input": "", "output": "import pandas as pd\n\ndf = pd.read_csv('data.csv')\nfiltered_df = df[df['age'] > 12]\nprint(filtered_df)"}
{"instruction": "Replace negative values with zero in the price column using numpy and pandas", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\ndf['price'] = np.where(df['price'] < 0, 0, df['price'])\nprint(df)"}
{"instruction": "Using numpy, calculate the mean of values in the quantity column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['quantity'].to_numpy()\nprint(np.mean(values))"}
{"instruction": "Using numpy, calculate the mean of values in the salary column from a CSV file", "input": "", "output": "import pandas as pd\nimport numpy as np\n\ndf = pd.read_csv('data.csv')\nvalues = df['salary'].to_numpy()\nprint(np.mean(values))"}