Update app.py

app.py

@@ -36,42 +36,43 @@ def to_excel(df):
 
 st.title("Exponential Smoothing Forecasting")
 # Upload Data Section
-uploaded_file = st.file_uploader("Choose a file")
-if uploaded_file is not None:
-    data = create_data()
-    unique_cities = data['City'].unique()
+# uploaded_file = st.file_uploader("Choose a file")
+# if uploaded_file is not None:
 
-    # Select a city
-    selected_city = st.selectbox('Select a City', unique_cities)
+data = create_data()
+unique_cities = data['City'].unique()
 
-    # Sliders for parameter adjustment
-    trend = st.select_slider('Select Trend', options=['add', 'mul', None])
-    damped_trend = st.checkbox('Damped Trend')
-    seasonal = st.select_slider('Select Seasonal', options=['add', 'mul', None])
-    seasonal_period = st.slider('Seasonal Period', 1, 24, 12)
+# Select a city
+selected_city = st.selectbox('Select a City', unique_cities)
 
-    # Display forecast with current parameters
-    city_data = data[data['City'] == selected_city]['Accident Count']
-    forecast, aic = run_exp_smoothing(city_data, trend, damped_trend, seasonal, seasonal_period)
-    if forecast is not None:
-        st.write(f"Forecast with AIC: {aic}")
-        st.line_chart(forecast)
+# Sliders for parameter adjustment
+trend = st.select_slider('Select Trend', options=['add', 'mul', None])
+damped_trend = st.checkbox('Damped Trend')
+seasonal = st.select_slider('Select Seasonal', options=['add', 'mul', None])
+seasonal_period = st.slider('Seasonal Period', 1, 24, 12)
 
-    # Grid search button
-    if st.button('Run Grid Search'):
-        best_aic = float('inf')
-        best_params = None
-        for param_set in product(['add', 'mul', None], [True, False], ['add', 'mul', None], [12]):
-            _, temp_aic = run_exp_smoothing(city_data, *param_set)
-            if temp_aic and temp_aic < best_aic:
-                best_aic = temp_aic
-                best_params = param_set
-        st.write(f"Best Parameters: {best_params} with AIC: {best_aic}")
+# Display forecast with current parameters
+city_data = data[data['City'] == selected_city]['Accident Count']
+forecast, aic = run_exp_smoothing(city_data, trend, damped_trend, seasonal, seasonal_period)
+if forecast is not None:
+    st.write(f"Forecast with AIC: {aic}")
+    st.line_chart(forecast)
 
-    # Export to Excel button
-    # if st.button('Export to Excel'):
-    #     df_to_export = pd.DataFrame(forecast)
-    #     excel_data = to_excel(df_to_export)
-    #     st.download_button(label='📥 Download Excel', data=excel_data, file_name='forecast.xlsx', mime='application/vnd.ms-excel')
+# Grid search button
+if st.button('Run Grid Search'):
+    best_aic = float('inf')
+    best_params = None
+    for param_set in product(['add', 'mul', None], [True, False], ['add', 'mul', None], [12]):
+        _, temp_aic = run_exp_smoothing(city_data, *param_set)
+        if temp_aic and temp_aic < best_aic:
+            best_aic = temp_aic
+            best_params = param_set
+    st.write(f"Best Parameters: {best_params} with AIC: {best_aic}")
+
+# Export to Excel button
+# if st.button('Export to Excel'):
+#     df_to_export = pd.DataFrame(forecast)
+#     excel_data = to_excel(df_to_export)
+#     st.download_button(label='📥 Download Excel', data=excel_data, file_name='forecast.xlsx', mime='application/vnd.ms-excel')