Update app.py

app.py

@@ -0,0 +1,79 @@
+import streamlit as st
+import pandas as pd
+import numpy as np
+from scipy import stats
+import openai
+
+def get_column_descriptions(df, openai_key):
+    openai.api_key = openai_key
+
+    descriptions = {}
+    for column in df.columns:
+        try:
+            # Generate a prompt for each column
+            prompt = f"Explain the meaning of a dataset column named '{column}' in the context of {df[column].dtype} data type."
+            response = openai.Completion.create(engine="text-davinci-003", prompt=prompt, max_tokens=60)
+            descriptions[column] = response.choices[0].text.strip()
+        except Exception as e:
+            descriptions[column] = f"Error in generating description: {e}"
+
+    return descriptions
+
+def analyze_dataframe(df):
+    info = df.info()
+    memory = df.memory_usage(deep=True)
+    # Missing values
+    missing_values = df.isnull().sum()
+    # Outliers (using Z-score for numerical columns)
+    outliers = df.select_dtypes(include=[np.number]).apply(lambda x: np.abs(stats.zscore(x)) > 3)
+    # Duplicates
+    duplicates = df[df.duplicated()]
+    # Statistics for each column
+    stats_df = df.describe(include='all')
+    return info, memory, missing_values, outliers, duplicates, stats_df
+
+def main():
+    st.title('Data Analysis App with GPT-3.5 Column Descriptions')
+
+    # API key for OpenAI
+    openai_key = st.sidebar.text_input("Enter your OpenAI API key", type="password")
+
+    uploaded_file = st.file_uploader("Upload your CSV or Excel file.", type=["csv", "xlsx"])
+    
+    if uploaded_file is not None:
+        # Read data
+        if uploaded_file.name.endswith('.csv'):
+            df = pd.read_csv(uploaded_file)
+        else:
+            df = pd.read_excel(uploaded_file)
+
+        # Analyze data
+        info, memory, missing_values, outliers, duplicates, stats_df = analyze_dataframe(df)
+
+        # Get column descriptions
+        if openai_key:
+            column_descriptions = get_column_descriptions(df, openai_key)
+            st.write("Column Descriptions:")
+            for col, desc in column_descriptions.items():
+                st.markdown(f"**{col}:** {desc}")
+                
+        st.write("Basic Information:")
+        st.text(info)
+
+        st.write("Memory Usage:")
+        st.write(memory)
+
+        st.write("Missing Values:")
+        st.write(missing_values)
+
+        st.write("Outliers:")
+        st.write(outliers)
+
+        st.write("Duplicates:")
+        st.write(duplicates)
+
+        st.write("Statistics:")
+        st.write(stats_df)
+
+if __name__ == "__main__":
+    main()