Update app.py
Browse files
app.py
CHANGED
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@@ -48,10 +48,10 @@ conn.close()
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'''
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# Create a sample DataFrame with 3,000 records and 20 columns
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num_records =
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num_columns = 20
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data = {
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f"column_{i}": np.random.randint(0, 100, num_records) for i in range(num_columns)
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}
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@@ -59,17 +59,17 @@ data = {
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# Randomize the year and city columns
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years = list(range(2000, 2023)) # Range of years
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cities = ["New York", "Los Angeles", "Chicago", "Houston", "Miami"] # List of cities
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#data["year"] = [random.choice(years) for _ in range(num_records)]
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#data["city"] = [random.choice(cities) for _ in range(num_records)]
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data = {
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"year": [1896, 1900, 1904, 2004, 2008, 2012],
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"city": ["athens", "paris", "st. louis", "athens", "beijing", "london"]
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}
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table = pd.DataFrame.from_dict(data)
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# Load the chatbot model
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'''
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# Create a sample DataFrame with 3,000 records and 20 columns
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num_records = 20
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num_columns = 20
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data = {
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f"column_{i}": np.random.randint(0, 100, num_records) for i in range(num_columns)
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}
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# Randomize the year and city columns
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years = list(range(2000, 2023)) # Range of years
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cities = ["New York", "Los Angeles", "Chicago", "Houston", "Miami"] # List of cities
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#data["year"] = [random.choice(years) for _ in range(num_records)]
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#data["city"] = [random.choice(cities) for _ in range(num_records)]
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table = pd.DataFrame(data)
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data = {
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"year": [1896, 1900, 1904, 2004, 2008, 2012],
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"city": ["athens", "paris", "st. louis", "athens", "beijing", "london"]
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}
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#table = pd.DataFrame.from_dict(data)
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# Load the chatbot model
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