Fix: Readme

streamlit_app.py

@@ -180,29 +180,83 @@ if st.session_state.authenticated:
                     with st.expander("View grouped data (first 10 rows)"):
                         st.dataframe(df_grouped.head(10))
                     
-                    st.write(f"📊 **Plotting {len(df_grouped)} actual data points (no gap filling)**")
+                    # Create complete date range and fill gaps
+                    date_range = pd.date_range(
+                        start=df_grouped['Reported Date'].min(),
+                        end=df_grouped['Reported Date'].max(),
+                        freq='D'
+                    )
+                    df_grouped = df_grouped.set_index('Reported Date').reindex(date_range).rename_axis('Reported Date').reset_index()
+                    
+                    # Fill missing values using the working method
+                    df_grouped['Arrivals (Tonnes)'] = df_grouped['Arrivals (Tonnes)'].fillna(method='ffill').fillna(method='bfill')
+                    df_grouped['Modal Price (Rs./Quintal)'] = df_grouped['Modal Price (Rs./Quintal)'].fillna(method='ffill').fillna(method='bfill')
+                    
+                    st.write(f"📊 **Plotting {len(df_grouped)} data points after filling date gaps**")
                     
                     st.subheader(f"📈 Trends for {selected_state} ({'Market: ' + selected_market if market_wise else 'State'})")
                     
                     if data_type == "Both":
+                        # Min-Max Scaling
                         scaler = MinMaxScaler()
-                        df_grouped[['Scaled Price', 'Scaled Arrivals']] = scaler.fit_transform(df_grouped[['Modal Price (Rs./Quintal)', 'Arrivals (Tonnes)']])
+                        df_grouped[['Scaled Price', 'Scaled Arrivals']] = scaler.fit_transform(
+                            df_grouped[['Modal Price (Rs./Quintal)', 'Arrivals (Tonnes)']]
+                        )
+
                         import plotly.graph_objects as go
                         fig = go.Figure()
-                        fig.add_trace(go.Scatter(x=df_grouped['Reported Date'], y=df_grouped['Scaled Price'], mode='lines', name='Scaled Price', line=dict(width=1, color='green')))
-                        fig.add_trace(go.Scatter(x=df_grouped['Reported Date'], y=df_grouped['Scaled Arrivals'], mode='lines', name='Scaled Arrivals', line=dict(width=1, color='blue')))
-                        fig.update_layout(title="Price and Arrivals Trend", xaxis_title='Date', yaxis_title='Scaled Values', template='plotly_white')
+
+                        fig.add_trace(go.Scatter(
+                            x=df_grouped['Reported Date'],
+                            y=df_grouped['Scaled Price'],
+                            mode='lines',
+                            name='Scaled Price',
+                            line=dict(width=1, color='green'),
+                            text=df_grouped['Modal Price (Rs./Quintal)'],
+                            hovertemplate='Date: %{x}<br>Scaled Price: %{y:.2f}<br>Actual Price: %{text:.2f}<extra></extra>'
+                        ))
+
+                        fig.add_trace(go.Scatter(
+                            x=df_grouped['Reported Date'],
+                            y=df_grouped['Scaled Arrivals'],
+                            mode='lines',
+                            name='Scaled Arrivals',
+                            line=dict(width=1, color='blue'),
+                            text=df_grouped['Arrivals (Tonnes)'],
+                            hovertemplate='Date: %{x}<br>Scaled Arrivals: %{y:.2f}<br>Actual Arrivals: %{text:.2f}<extra></extra>'
+                        ))
+
+                        fig.update_layout(
+                            title="Price and Arrivals Trend",
+                            xaxis_title='Date',
+                            yaxis_title='Scaled Values',
+                            template='plotly_white'
+                        )
                         st.plotly_chart(fig, use_container_width=True)
                     elif data_type == "Price":
+                        # Plot Modal Price
                         import plotly.graph_objects as go
                         fig = go.Figure()
-                        fig.add_trace(go.Scatter(x=df_grouped['Reported Date'], y=df_grouped['Modal Price (Rs./Quintal)'], mode='lines', name='Modal Price', line=dict(width=1, color='green')))
+                        fig.add_trace(go.Scatter(
+                            x=df_grouped['Reported Date'],
+                            y=df_grouped['Modal Price (Rs./Quintal)'],
+                            mode='lines',
+                            name='Modal Price',
+                            line=dict(width=1, color='green')
+                        ))
                         fig.update_layout(title="Modal Price Trend", xaxis_title='Date', yaxis_title='Price (/Quintall)', template='plotly_white')
                         st.plotly_chart(fig, use_container_width=True)
-                    else:
+                    elif data_type == "Volume":
+                        # Plot Arrivals (Tonnes)
                         import plotly.graph_objects as go
                         fig = go.Figure()
-                        fig.add_trace(go.Scatter(x=df_grouped['Reported Date'], y=df_grouped['Arrivals (Tonnes)'], mode='lines', name='Arrivals', line=dict(width=1, color='blue')))
+                        fig.add_trace(go.Scatter(
+                            x=df_grouped['Reported Date'],
+                            y=df_grouped['Arrivals (Tonnes)'],
+                            mode='lines',
+                            name='Arrivals',
+                            line=dict(width=1, color='blue')
+                        ))
                         fig.update_layout(title="Arrivals Trend", xaxis_title='Date', yaxis_title='Volume (in Tonnes)', template='plotly_white')
                         st.plotly_chart(fig, use_container_width=True)
                 else: