changes

pages/stock_prediction.py

@@ -106,56 +106,3 @@ st.dataframe(df_1.style.set_properties(**{'font-size': '20px'}),width=1000)
 forecast = pd.concat([rolling_price,forecast])
 
 
-# def Moving_average_forecast(forecast):
-#     # Ensure enough data exists
-#     if len(forecast) <= 30:
-#         return "Not enough data to plot."
-
-#     # Convert index to datetime if needed
-#     if not isinstance(forecast.index, pd.DatetimeIndex):
-#         forecast.index = pd.to_datetime(forecast.index)
-
-#     fig = go.Figure()
-
-#     # First trace: Past close prices
-#     if len(forecast.index[:-30]) > 0:
-#         fig.add_trace(go.Scatter(
-#             x=forecast.index[:-30],
-#             y=forecast['Close'].iloc[:-30],
-#             mode='lines',
-#             name='Close Price',
-#             line=dict(width=2, color='blue')
-#         ))
-#     else:
-#         st.warning("No data available for past close prices.")
-
-#     # Second trace: Future close prices
-#     if len(forecast.index[-31:]) > 0:
-#         fig.add_trace(go.Scatter(
-#             x=forecast.index[-31:],
-#             y=forecast['Close'].iloc[-31:],
-#             mode='lines',
-#             name='Future Close Price',
-#             line=dict(width=2, color='red')
-#         ))
-#     else:
-#         st.warning("No data available for future close prices.")
-
-#     fig.update_layout(
-#         title="Moving Average Forecast",
-#         xaxis_title="Date",
-#         yaxis_title="Close Price",
-#         height=500,
-#         plot_bgcolor='white',
-#         paper_bgcolor='#E1EFFF',
-#         legend=dict(yanchor='top', xanchor='right')
-#     )
-
-#     return fig
-
-# # Plot with debug checks
-# fig = Moving_average_forecast(forecast.iloc[150:])
-# if isinstance(fig, str):
-#     st.warning(fig)
-# else:
-#     st.plotly_chart(fig, use_container_width=True)