Update app.py

app.py

@@ -101,26 +101,40 @@ moving_avg_slider = pn.widgets.IntSlider(name='Moving Average Window', start=1,
 def create_plot(subgroup, date_range, moving_av_window):
     start_date, end_date = date_range[0].date(), date_range[1].date()  # Convert to date
     data = df2[(df2['subgroup'] == subgroup) & (df2['choice'] == "approve")  & (df2['timestamp'].dt.date.between(start_date, end_date))]
-    # filtered_data = df2[(df2['subgroup'] == subgroup) & (df2['timestamp'].dt.date.between(date_range[0], date_range[1]))]
+    
+    min_rate = df2['rate'].min()
+    max_rate = df2['rate'].max()
+    
     data = data.sort_values('timestamp')
     data['moving_avg'] = data['rate'].rolling(window=moving_av_window, min_periods=1).mean()
 
-    chart = alt.Chart(data).mark_line().encode(
-        x='timestamp:T',
-        y=alt.Y('moving_avg:Q', scale=alt.Scale(zero=False)),
-        color='choice:N',
-        tooltip=['timestamp:T', 'rate:Q', 'moving_avg:Q', 'choice:N']
-    ).properties(width=600, height=400).interactive()
+    # Line chart for moving average
+    line = alt.Chart(data).mark_line(interpolate='natural').encode(
+        x=alt.X('timestamp:T', axis=alt.Axis(title='', format='%b %d, %Y')),
+        y=alt.Y('moving_avg:Q', axis=alt.Axis(title='approve,mov_avg'), scale=alt.Scale(domain=[min_rate, max_rate])),
+        color=alt.value('red')
+    )
 
-    return chart
+    # Scatter plot for individual data points
+    points = alt.Chart(data).mark_point().encode(
+        x=alt.X('timestamp:T'),
+        y=alt.Y('rate:Q', axis=alt.Axis(title='approve,mov_avg'), scale=alt.Scale(domain=[min_rate, max_rate])),
+        color=alt.value('gray'),
+        tooltip=['timestamp:T', 'rate:Q']
+    )
+
+    # Combine line chart and scatter plot
+    plot = alt.layer(points, line).resolve_scale(y='shared')
+
+    return plot
 
 # Main layout
 main_layout = pn.Column(
     "# Polling Data Interactive Visualization",
+    pn.panel(create_plot, reactive=True)
     subgroup_select,
     date_slider,
     moving_avg_slider,
-    pn.panel(create_plot, reactive=True)
 )
 
 # Create a basic template