# Import panel and vega datasets import panel as pn import vega_datasets # Enable Panel extensions pn.extension() template = pn.template.BootstrapTemplate( title='SI649 Altair3', ) maincol = pn.Column() # Define a function to create and return a plot 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'].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', size=2).encode( x='timestamp:T', y='mov_avg:Q' ) # Scatter plot with individual polls 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 + line_chart # Return the combined chart return plot # # Create the selection widget 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 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=100, value=1) # Bind the widgets to the create_plot function 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 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 template.servable(title="SI649 Altair3")