Create app.py

app.py

@@ -0,0 +1,146 @@
+import gradio as gr
+import pandas as pd
+from ydata_profiling import ProfileReport
+import sweetviz as sv
+from dataprep.eda import create_report
+import io
+
+class DataAnalyzer:
+    def __init__(self):
+        self.current_df = None
+    
+    def generate_profile_report(self, df, minimal=False):
+        profile = ProfileReport(
+            df,
+            minimal=minimal,
+            title="Pandas Profiling Report",
+            explorative=True,
+            dark_mode=True
+        )
+        # Get HTML directly as string
+        return profile.to_html()
+    
+    def generate_sweetviz_report(self, df):
+        report = sv.analyze(df)
+        # Use StringIO to capture the HTML output
+        html_io = io.StringIO()
+        report.show_html(filepath=html_io, open_browser=False)
+        return html_io.getvalue()
+    
+    def generate_dataprep_report(self, df):
+        report = create_report(df)
+        # Get HTML directly as string
+        return report.html()
+    
+    def get_dataset_info(self, df):
+        return {
+            "Rows": len(df),
+            "Columns": len(df.columns),
+            "Memory Usage (MB)": df.memory_usage(deep=True).sum() / 1024**2,
+            "Missing Values": df.isnull().sum().sum(),
+            "Data Types": df.dtypes.value_counts().to_dict()
+        }
+
+def create_interface():
+    analyzer = DataAnalyzer()
+    
+    with gr.Blocks(theme=gr.themes.Soft()) as demo:
+        gr.Markdown("""
+        # Data Analysis Dashboard
+        Upload your CSV file to generate interactive analysis reports
+        """)
+        
+        with gr.Row():
+            file_input = gr.File(label="Upload CSV")
+            dataset_info = gr.JSON(label="Dataset Information")
+        
+        with gr.Row():
+            report_type = gr.Radio(
+                choices=["Full", "Minimal"],
+                value="Full",
+                label="Report Type"
+            )
+        
+        with gr.Tabs():
+            with gr.TabItem("Pandas Profiling"):
+                profile_html = gr.HTML()
+            with gr.TabItem("Sweetviz"):
+                sweet_html = gr.HTML()
+            with gr.TabItem("DataPrep"):
+                prep_html = gr.HTML()
+        
+        def process_file(file, report_type):
+            if file is None:
+                return None, None, None, None
+            
+            try:
+                df = pd.read_csv(file.name)
+                analyzer.current_df = df
+                
+                # Get dataset info
+                info = analyzer.get_dataset_info(df)
+                
+                # Generate reports
+                minimal = report_type == "Minimal"
+                
+                with gr.Progress() as progress:
+                    progress(0, desc="Generating Pandas Profiling report...")
+                    profile_html = analyzer.generate_profile_report(df, minimal)
+                    
+                    progress(0.33, desc="Generating Sweetviz report...")
+                    sweet_html = analyzer.generate_sweetviz_report(df)
+                    
+                    progress(0.66, desc="Generating DataPrep report...")
+                    prep_html = analyzer.generate_dataprep_report(df)
+                    
+                    progress(1.0, desc="Done!")
+                
+                return (
+                    info,
+                    profile_html,
+                    sweet_html,
+                    prep_html
+                )
+                
+            except Exception as e:
+                return str(e), None, None, None
+        
+        file_input.change(
+            fn=process_file,
+            inputs=[file_input, report_type],
+            outputs=[dataset_info, profile_html, sweet_html, prep_html]
+        )
+        
+        report_type.change(
+            fn=process_file,
+            inputs=[file_input, report_type],
+            outputs=[dataset_info, profile_html, sweet_html, prep_html]
+        )
+    
+    return demo
+
+# Add custom CSS for better HTML rendering
+custom_css = """
+<style>
+.report-container {
+    width: 100%;
+    height: 800px;
+    overflow: auto;
+}
+.report-container iframe {
+    width: 100%;
+    height: 100%;
+    border: none;
+}
+</style>
+"""
+
+# Launch the interface
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.launch(
+        share=True,  # Enable sharing
+        height=1000,  # Set interface height
+        show_error=True,  # Show detailed error messages
+        custom_css=custom_css  # Apply custom styling
+    )