Update app.py

app.py

@@ -5,70 +5,71 @@ import vega_datasets
 
 # Enable Panel extensions
 pn.extension()
+pn.extension('vega', 'tabulator')
+
 template = pn.template.BootstrapTemplate(
-    title='SI649 Lab7',
+    title='SI649 Altair3',
 )
 
+maincol = pn.Column()
+
 # Define a function to create and return a plot
-def create_plot(subgroup):
-# def create_plot(subgroup, date_range, moving_av_window):
+def create_plot(subgroup, date_range, moving_av_window):
 
     # Apply any required transformations to the data in pandas)
     filtered_df = df2_approve[df2_approve['subgroup'] == subgroup]
-    # filtered_df = filtered_df[(filtered_df['timestamp'] >= date_range[0]) & (filtered_df['timestamp'] <= date_range[1])]
-    # filtered_df['Smoothed_Rate'] = filtered_df['rate'].rolling(window=moving_av_window, min_periods=1).mean().shift()
+    filtered_df = filtered_df[(filtered_df['timestamp'].dt.date >= date_range[0]) & (filtered_df['timestamp'].dt.date <= date_range[1])]
+    filtered_df['mov_avg'] = filtered_df['rate'].rolling(window=moving_av_window, min_periods=1).mean().shift(moving_av_window//2)
 
     # Line chart
-    # line_chart = alt.Chart(filtered_df).mark_line(color='red').encode(
-    #     x='timestamp:T',
-    #     y='Smoothed_Rate:Q'
-    # )
+    line_chart = alt.Chart(filtered_df).mark_line(color='red', size=2).encode(
+        x='timestamp:T',
+        y='mov_avg:Q'
+    )
 
     # Scatter plot with individual polls
-    scatter_plot = alt.Chart(filtered_df).mark_point(color='gray', size=2, opacity=0.7).encode(
+    scatter_plot = alt.Chart(filtered_df).mark_point(color='grey', size=2, opacity=0.7).encode(
         x='timestamp:T',
         y='rate:Q'
     )
 
     # Put them togetehr
-    plot = scatter_plot
+    plot = scatter_plot + line_chart
     
     # Return the combined chart
     return plot
-
-# date_range = ('2021-04-01', '2023-01-01')
-
-# create_plot('All polls', date_range, 3)
     
 
 # # Create the selection widget
-# subgroup_widget = pn.widgets.Select(options=['All polls', 'Adults', 'Voters'], name='Subgroup')
 select = pn.widgets.Select(name='Select', options=['All polls', 'Adults', 'Voters'])
 
 
 # # Create the slider for the date range
-# date_range_slider = pn.widgets.DateRangeSlider(name='Date Range')
-# date_range_slider = pn.widgets.DateRangeSlider(
-#     name='Date Range Slider',
-#     start=dt.datetime(2017, 1, 1), end=dt.datetime(2019, 1, 1),
-#     value=(dt.datetime(2017, 1, 1), dt.datetime(2018, 1, 10)),
-#     step=2
-# )
+date_range_slider = pn.widgets.DateRangeSlider(
+    name='Date Range Slider',
+    start=df2['timestamp'].dt.date.min(), end=df2['timestamp'].dt.date.max(),
+    value=(df2['timestamp'].dt.date.min(), df2['timestamp'].dt.date.max()),
+    step=1
+)
 
 
 # # Create the slider for the moving average window
-# moving_av_slider = pn.widgets.IntSlider(name='Moving Average Window', start=1, end=10, value=3)
+moving_av_slider = pn.widgets.IntSlider(name='Moving Average Window', start=1, end=100, value=1)
 
-# create_plot(subgroup_widget, date_range_slider, moving_av_slider)
 
 # Bind the widgets to the create_plot function
-final = pn.bind(create_plot,select)
-template.main.append(final)
-
+final = pn.Row(pn.bind(create_plot, 
+                       subgroup=select, 
+                       date_range=date_range_slider, 
+                       moving_av_window=moving_av_slider))
 
 
 # # Combine everything in a Panel Column to create an app
-# app = pn.Column(subgroup_widget, date_range_slider, moving_av_slider, update_plot)
+maincol.append(final)
+maincol.append(select)
+maincol.append(date_range_slider)
+maincol.append(moving_av_slider)
+template.main.append(maincol)
 
 # # set the app to be servable
-# app.servable()
+template.show()