Update app.py

app.py

@@ -19,7 +19,9 @@ class DataAnalyzer:
         self.AV = AutoViz_Class()
         
     def generate_sweetviz_report(self, df):
-        self.df = df
+        if df is None:
+            return "Please upload a dataset first"
+        
         report = sv.analyze(df)
         report_path = os.path.join(self.temp_dir, "report.html")
         report.show_html(report_path, open_browser=False)
@@ -43,20 +45,21 @@ class DataAnalyzer:
         return html_with_table
 
     def generate_autoviz_report(self, df):
-        """Generate AutoViz report with proper sequence"""
+        if df is None:
+            return "Please upload a dataset first"
+            
         viz_temp_dir = os.path.join(self.temp_dir, "autoviz_output")
         if os.path.exists(viz_temp_dir):
             shutil.rmtree(viz_temp_dir)
         os.makedirs(viz_temp_dir)
 
         try:
-            # Proper AutoViz sequence
-            plt.close('all')  # Close any existing plots
+            plt.close('all')
             dfte = self.AV.AutoViz(
                 filename='',
                 sep=',',
                 depVar='',
-                dfte=df,  # Pass DataFrame directly
+                dfte=df,
                 header=0,
                 verbose=0,
                 lowess=False,
@@ -66,7 +69,6 @@ class DataAnalyzer:
                 save_plot_dir=viz_temp_dir
             )
 
-            # Collect generated HTML files
             html_parts = []
             if os.path.exists(viz_temp_dir):
                 for file in sorted(os.listdir(viz_temp_dir)):
@@ -98,60 +100,64 @@ def create_interface():
     with gr.Blocks(theme=gr.themes.Soft()) as demo:
         gr.Markdown("# Data Analysis Dashboard")
         
-        # Define all outputs first
-        data_preview = gr.Dataframe(label="Data Preview")
-        report_html = gr.HTML(label="Sweetviz Report")
-        autoviz_html = gr.HTML(label="AutoViz Report")
-        column_dropdown = gr.Dropdown(
-            label="Select Categorical Column",
-            choices=[],
-            interactive=True
-        )
+        # Store the dataframe in a state variable
+        current_df = gr.State(None)
         
         with gr.Tabs():
+            # First Tab: Data Upload & Preview
             with gr.TabItem("Data Upload & Preview"):
-                file_input = gr.File(label="Upload CSV")
-            
-            with gr.TabItem("AutoViz Analysis"):
-                gr.Markdown("""
-                ### AutoViz Analysis
-                Automatic visualization of your dataset
-                """)
+                with gr.Row():
+                    file_input = gr.File(label="Upload CSV")
+                data_preview = gr.Dataframe(label="Data Preview", interactive=False)
+                
+                def load_data(file):
+                    if file is None:
+                        return None, None
+                    try:
+                        df = pd.read_csv(file.name)
+                        return df.head(), df
+                    except Exception as e:
+                        return None, None
+                
+                file_input.change(
+                    fn=load_data,
+                    inputs=[file_input],
+                    outputs=[data_preview, current_df]
+                )
             
-            with gr.TabItem("Categorical Analysis"):
-                encoder_dropdown = gr.Dropdown(
-                    label="Select Encoder",
-                    choices=['binary', 'onehot', 'catboost', 'count'],
-                    value='binary',
-                    interactive=True
+            # Second Tab: Sweetviz Analysis
+            with gr.TabItem("Sweetviz Analysis"):
+                with gr.Row():
+                    sweetviz_button = gr.Button("Generate Sweetviz Report")
+                sweetviz_output = gr.HTML(label="Sweetviz Report")
+                
+                def generate_sweetviz(df):
+                    if df is None:
+                        return "Please upload a dataset first"
+                    return analyzer.generate_sweetviz_report(df)
+                
+                sweetviz_button.click(
+                    fn=generate_sweetviz,
+                    inputs=[current_df],
+                    outputs=[sweetviz_output]
                 )
-                plot_output = gr.Image(label="UMAP Visualization")
-
-        def process_file(file):
-            if file is None:
-                return None, None, None, gr.Dropdown(choices=[])
             
-            try:
-                df = pd.read_csv(file.name)
-                preview = df.head()
-                sweetviz_report = analyzer.generate_sweetviz_report(df)
-                autoviz_report = analyzer.generate_autoviz_report(df)
-                cat_columns = df.select_dtypes(include=['object', 'category']).columns.tolist()
+            # Third Tab: AutoViz Analysis
+            with gr.TabItem("AutoViz Analysis"):
+                with gr.Row():
+                    autoviz_button = gr.Button("Generate AutoViz Report")
+                autoviz_output = gr.HTML(label="AutoViz Report")
+                
+                def generate_autoviz(df):
+                    if df is None:
+                        return "Please upload a dataset first"
+                    return analyzer.generate_autoviz_report(df)
                 
-                return (
-                    preview,
-                    sweetviz_report,
-                    autoviz_report,
-                    gr.Dropdown(choices=cat_columns)
+                autoviz_button.click(
+                    fn=generate_autoviz,
+                    inputs=[current_df],
+                    outputs=[autoviz_output]
                 )
-            except Exception as e:
-                return None, f"Error: {str(e)}", f"Error: {str(e)}", gr.Dropdown(choices=[])
-
-        file_input.change(
-            fn=process_file,
-            inputs=[file_input],
-            outputs=[data_preview, report_html, autoviz_html, column_dropdown]
-        )
 
     return demo