Improve revenue chart: use DataFrame-based histogram

streamlit_app/app.py

@@ -516,34 +516,42 @@ if page == "📊 Overview":
             # Filter to positive values only
             revenue_values = revenue_values[revenue_values > 0].dropna()
             
-            if not revenue_values.empty and len(revenue_values) > 5:
+            if revenue_values.empty:
+                st.info(f"No positive revenue values found in {best_col}")
+            elif len(revenue_values) <= 5:
+                st.info("Insufficient data for distribution chart")
+            else:
                 try:
-                    # Create histogram
+                    # Create histogram using DataFrame format for better Streamlit compatibility
+                    nbins = min(30, max(5, len(revenue_values) // 10))
+                    df_hist = pd.DataFrame({'Revenue': revenue_values})
+                    
                     fig = px.histogram(
-                        revenue_values,
-                        nbins=min(30, len(revenue_values)//5),
+                        df_hist,
+                        x='Revenue',
+                        nbins=nbins,
                         title=f"Revenue Distribution - {best_col}",
-                        color_discrete_sequence=['#636EFA'],
-                        labels={'value': best_col, 'count': 'Count'}
+                        color_discrete_sequence=['#636EFA']
                     )
                     fig.update_layout(
                         height=400,
                         xaxis_title=best_col,
                         yaxis_title="Count",
-                        hovermode='x unified'
+                        hovermode='x unified',
+                        showlegend=False
                     )
                     fig.update_traces(marker=dict(line=dict(width=0)))
                     st.plotly_chart(fig, use_container_width=True)
                 except Exception as e:
-                    st.warning(f"Could not create histogram: {e}")
-                    # Fallback: show summary stats
-                    st.metric("Average Revenue", f"₹{revenue_values.mean():,.0f}")
-                    st.metric("Median Revenue", f"₹{revenue_values.median():,.0f}")
-                    st.metric("Max Revenue", f"₹{revenue_values.max():,.0f}")
-            elif revenue_values.empty:
-                st.info(f"No positive revenue values found in {best_col}")
-            else:
-                st.info("Insufficient data for distribution chart")
+                    st.error(f"Error creating histogram: {str(e)}")
+                    # Fallback: show summary stats in columns
+                    col_stats1, col_stats2, col_stats3 = st.columns(3)
+                    with col_stats1:
+                        st.metric("Average", f"₹{revenue_values.mean():,.0f}")
+                    with col_stats2:
+                        st.metric("Median", f"₹{revenue_values.median():,.0f}")
+                    with col_stats3:
+                        st.metric("Max", f"₹{revenue_values.max():,.0f}")
         else:
             st.info("Revenue column not found. Add a revenue/amount column to plot this chart.")