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app.py

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+import pandas as pd
+import gradio as gr
+
+def analyze_csv(file_obj):
+    # 1. Read the uploaded CSV
+    df = pd.read_csv(file_obj.name)
+    
+    # 2. Extract basic shape
+    row_count = len(df)
+    col_count = len(df.columns)
+    
+    # 3. Automatically calculate statistics (mean, min, max) and round to 2 decimals
+    summary_stats = df.describe().round(2)
+    
+    # 4. Grab the first 5 rows for a preview
+    head_df = df.head()
+    
+    # 5. Format the text report
+    report = f"### 📌 Data Overview\n* **Total Rows:** {row_count}\n* **Total Columns:** {col_count}\n\n"
+    report += "The tool has automatically processed the mathematical summary and extracted a data preview below."
+    
+    return report, summary_stats, head_df
+
+# Building the modern UI 
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 📊 Automated Business Data Analyzer")
+    gr.Markdown("Upload any raw CSV file to instantly generate a statistical breakdown.")
+    
+    with gr.Row():
+        file_input = gr.File(label="Upload CSV File here", file_types=[".csv"])
+        
+    with gr.Row():
+        text_output = gr.Markdown()
+        
+    with gr.Row():
+        stats_output = gr.Dataframe(label="Mathematical Summary (Averages, Min, Max)")
+        
+    with gr.Row():
+        head_output = gr.Dataframe(label="Raw Data Preview (First 5 Rows)")
+        
+    # Connect the upload button to the logic function
+    file_input.upload(fn=analyze_csv, inputs=file_input, outputs=[text_output, stats_output, head_output])
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt.txt

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+pandas
+gradio