Revert "mv1"

This reverts commit a4d09ea9c680bd873fb2635776f3127798fea78b.

app.py

@@ -64,19 +64,6 @@ def generate_chart(data: Union[Dict, List[Dict], pd.DataFrame],
         A Plotly Figure object (interactive) or None on error
     """
     try:
-        # Debug: Log the input data
-        logger.info(f"Generating {chart_type} chart with x={x}, y={y}")
-        logger.info(f"Input data type: {type(data)}")
-        if hasattr(data, 'head'):  # It's a DataFrame
-            logger.info(f"DataFrame columns: {data.columns.tolist()}")
-            logger.info(f"Data sample:\n{data.head(2).to_string()}")
-        elif isinstance(data, (list, dict)):
-            logger.info(f"Data sample: {str(data)[:500]}...")
-            
-        # Validate data
-        if data is None or (hasattr(data, 'empty') and data.empty) or (isinstance(data, (list, dict)) and not data):
-            logger.error("No data provided to generate_chart")
-            return None
         # Convert data to DataFrame if it's a list of dicts
         if isinstance(data, list):
             df = pd.DataFrame(data)
@@ -90,50 +77,17 @@ def generate_chart(data: Union[Dict, List[Dict], pd.DataFrame],
             
         # Generate the appropriate chart type
         fig = None
-        try:
-            if chart_type == 'bar':
-                fig = px.bar(df, x=x, y=y, title=title)
-            elif chart_type == 'line':
-                fig = px.line(df, x=x, y=y, title=title)
-            elif chart_type == 'pie':
-                fig = px.pie(df, names=x, values=y, title=title, hole=0)
-            elif chart_type == 'scatter':
-                # Ensure we have valid numeric data for scatter plot
-                if df[x].isnull().any() or df[y].isnull().any():
-                    logger.error(f"Null values found in data for scatter plot. x: {df[x].isnull().sum()}, y: {df[y].isnull().sum()}")
-                    # Try to convert to numeric, coercing errors
-                    df[x] = pd.to_numeric(df[x], errors='coerce')
-                    df[y] = pd.to_numeric(df[y], errors='coerce')
-                    # Drop rows with NaN values
-                    df = df.dropna(subset=[x, y])
-                    if df.empty:
-                        logger.error("No valid numeric data points after cleaning")
-                        return None
-                    logger.info("Data cleaned for scatter plot")
-                fig = px.scatter(df, x=x, y=y, title=title)
-            elif chart_type == 'histogram':
-                fig = px.histogram(df, x=x, title=title)
-            else:
-                logger.error(f"Unsupported chart type: {chart_type}")
-                return None
-                
-            if fig is None:
-                logger.error("Failed to generate figure")
-                return None
-                
-        except Exception as e:
-            logger.error(f"Error generating {chart_type} chart: {str(e)}", exc_info=True)
-            # Try to provide a more helpful error message
-            if 'NoneType' in str(e) and 'heuristic' in str(e):
-                logger.error("A* search heuristic failed - likely due to invalid or missing coordinate data")
-                # Try to identify which column has the issue
-                for col in [x, y]:
-                    if col and col in df.columns:
-                        null_count = df[col].isnull().sum()
-                        if null_count > 0:
-                            logger.error(f"Column '{col}' has {null_count} null values")
-                        if not pd.api.types.is_numeric_dtype(df[col]):
-                            logger.error(f"Column '{col}' is not numeric. Type: {df[col].dtype}")
+        if chart_type == 'bar':
+            fig = px.bar(df, x=x, y=y, title=title)
+        elif chart_type == 'line':
+            fig = px.line(df, x=x, y=y, title=title)
+        elif chart_type == 'pie':
+            fig = px.pie(df, names=x, values=y, title=title, hole=0)
+        elif chart_type == 'scatter':
+            fig = px.scatter(df, x=x, y=y, title=title)
+        elif chart_type == 'histogram':
+            fig = px.histogram(df, x=x, title=title)
+        else:
             return None
         
         # Update layout