Update app.py

app.py

@@ -4,114 +4,74 @@ import pandas as pd
 import altair as alt
 from vega_datasets import data
 
-# we want to use bootstrap/template, tell Panel to load up what we need
-pn.extension(design='bootstrap')
+# Enable Panel extensions
+pn.extension()
+# pn.extension('vega', 'tabulator')
+# pn.extension(design='bootstrap')
+# pn.extension('vega')
 
-# we want to use vega, tell Panel to load up what we need
-pn.extension('vega')
-
-# create a basic template using bootstrap
 template = pn.template.BootstrapTemplate(
-    title='SI649 Walkthrough',
+    title='SI649 Altair3',
 )
 
-# the main column will hold our key content
-maincol = pn.Column()
-
-# add some markdown to the main column
-maincol.append("# Markdown Title")
-maincol.append("I can format in cool ways. Like **bold** or *italics* or ***both*** or ~~strikethrough~~ or `code` or [links](https://panel.holoviz.org)")
-maincol.append("I am writing a link [to the streamlit documentation page](https://docs.streamlit.io/en/stable/api.html)")
-maincol.append('![alt text](https://upload.wikimedia.org/wikipedia/commons/thumb/3/3e/Irises-Vincent_van_Gogh.jpg/314px-Irises-Vincent_van_Gogh.jpg)')
+# Define a function to create and return a plot
+def create_plot(subgroup, date_range, moving_av_window):
 
-# load up a dataframe and show it in the main column
-cars_url = "https://raw.githubusercontent.com/altair-viz/vega_datasets/master/vega_datasets/_data/cars.json"
-cars = pd.read_json(cars_url)
-temps = data.seattle_weather()
+    # 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).mean().shift(moving_av_window//2)
 
-maincol.append(temps.head(10))
-
-# create a basic chart
-hp_mpg = alt.Chart(cars).mark_circle(size=80).encode(
-    x='Horsepower:Q',
-    y='Miles_per_Gallon:Q',
-    color='Origin:N'
-)
-
-# dispaly it in the main column
-# maincol.append(hp_mpg)
+    # Line chart
+    line_chart = alt.Chart(filtered_df).mark_line(color='red', size=2).encode(
+        x='timestamp:T',
+        y='mov_avg:Q'
+    )
 
-# create a basic slider
-simpleslider = pn.widgets.IntSlider(name='Simple Slider', start=0, end=100, value=0)
+    # 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'
+    )
 
-# generate text based on slider value
-def square(x):
-    return f'{x} squared is {x**2}'
+    # 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'])
 
-# bind the slider to the function and hold the output in a row
-row = pn.Column(pn.bind(square,simpleslider))
 
-# add both slider and row
-maincol.append(simpleslider)
-maincol.append(row)
+# # Create the slider for the date range
+date_range_slider = pn.widgets.DateRangeSlider(
+    name='Date Range Slider',
+    start=df2_approve['timestamp'].dt.date.min(), end=df2_approve['timestamp'].dt.date.max(),
+    value=(df2_approve['timestamp'].dt.date.min(), df2_approve['timestamp'].dt.date.max()),
+    step=1
+)
 
-# variable to track state of visualization
-flip = False
 
-# function to either return the vis or a message
-def makeChartVisible(val):
-    global flip  # grab the variable outside the function
-    if (flip == True):
-        flip = not flip             # flip to False
-        return pn.pane.Vega(hp_mpg) # return the vis
-    else:
-        flip = not flip             # flip to true and return text
-        return pn.panel("Click the button to see the chart")
-    
-# add a button and then create the binding
-btn = pn.widgets.Button(name='Click me')
-row = pn.Row(pn.bind(makeChartVisible, btn))
-
-# add button and new row to main column
-maincol.append(btn)
-maincol.append(row)
-
-# create a base chart
-basechart = alt.Chart(cars).mark_circle(size=80,opacity=0.5).encode(
-    x='Horsepower:Q',
-    y='Acceleration:Q',
-    color="Origin:N"
-)
+# # Create the slider for the moving average window
+moving_av_slider = pn.widgets.IntSlider(name='Moving Average Window', start=1, end=100, value=1)
 
-# create something to hold the base chart
-currentoption = pn.panel(basechart)
 
-# create a selection widget
-select = pn.widgets.Select(name='Select', options=['Horsepower','Acceleration','Miles_per_Gallon'])
+# 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))
 
-# create a function to modify the basechart that is being
-# held in currentoption
-def changeOption(val):
-    # grab what's there now
-    chrt = currentoption.object
-    # change the encoding based on val
-    chrt = chrt.encode(
-        y=val+":Q"
-    )
-    # replace old chart in currentoption with new one
-    currentoption.object = chrt
 
-# append the selection
+# # Combine everything in a Panel Column to create an app
+maincol=pn.Column()
+maincol.append(final)
 maincol.append(select)
-# append the binding (in thise case nothing is being returned by changeOption, so...)
-chartchange = pn.Row(pn.bind(changeOption, select))
-# ... we need to also add the chart
-maincol.append(chartchange)
-maincol.append(currentoption)
-
-# add the main column to the template
+maincol.append(date_range_slider)
+maincol.append(moving_av_slider)
 template.main.append(maincol)
 
 # Indicate that the template object is the "application" and serve it
-template.servable(title="SI649 Walkthrough")
+template.servable(title="SI649 Altair3")