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Update app.py

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  1. app.py +90 -65
app.py CHANGED
@@ -1,92 +1,117 @@
1
- # Import panel and vega datasets
2
-
3
  import panel as pn
4
- import vega_datasets
5
-
6
  import pandas as pd
7
  import altair as alt
8
- # import numpy as np
9
- # import pprint
10
- import datetime as dt
11
  from vega_datasets import data
12
- # import matplotlib.pyplot as plt
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-
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-
15
- df2=pd.read_csv("https://raw.githubusercontent.com/dallascard/SI649_public/main/altair_hw3/approval_topline.csv")
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-
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- df2['timestamp']=pd.to_datetime(df2['timestamp'])
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- df2=pd.melt(df2, id_vars=['president', 'subgroup', 'timestamp'], value_vars=['approve','disapprove']).rename(columns={'variable':'choice', 'value':'rate'})
19
 
20
-
21
- # Enable Panel extensions
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- # pn.extension()
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- # pn.extension('vega', 'tabulator')
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  pn.extension(design='bootstrap')
 
 
25
  pn.extension('vega')
26
 
 
27
  template = pn.template.BootstrapTemplate(
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- title='SI649 Altair3',
29
  )
30
 
31
- # Define a function to create and return a plot
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- def create_plot(subgroup, date_range, moving_av_window):
33
 
34
- # Apply any required transformations to the data in pandas)
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- df2_approve = df2[df2['choice'] == 'approve']
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- filtered_df = df2_approve[df2_approve['subgroup'] == subgroup]
37
- filtered_df = filtered_df[(filtered_df['timestamp'].dt.date >= date_range[0]) & (filtered_df['timestamp'].dt.date <= date_range[1])]
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- filtered_df['mov_avg'] = filtered_df['rate'].rolling(window=moving_av_window).mean().shift(-moving_av_window//2)
39
 
40
- # Line chart
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- line_chart = alt.Chart(filtered_df).mark_line(color='red', size=2).encode(
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- x='timestamp:T',
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- y='mov_avg:Q'
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- )
45
 
46
- # Scatter plot with individual polls
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- scatter_plot = alt.Chart(filtered_df).mark_point(color='grey', size=2, opacity=0.7).encode(
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- x='timestamp:T',
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- y='rate:Q'
50
- )
51
 
52
- # Put them togetehr
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- plot = scatter_plot + line_chart
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-
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- # Return the combined chart
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- return pn.pane.Vega(plot)
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-
58
 
59
- # # Create the selection widget
60
- select = pn.widgets.Select(name='Select', options=['All polls', 'Adults', 'Voters'])
61
 
 
 
62
 
63
- # # Create the slider for the date range
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- date_range_slider = pn.widgets.DateRangeSlider(
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- name='Date Range Slider',
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- start=df2['timestamp'].dt.date.min(), end=df2['timestamp'].dt.date.max(),
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- value=(df2['timestamp'].dt.date.min(), df2['timestamp'].dt.date.max()),
68
- step=1
69
- )
70
 
 
 
 
71
 
72
- # # Create the slider for the moving average window
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- moving_av_slider = pn.widgets.IntSlider(name='Moving Average Window', start=1, end=100, value=1)
74
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
75
 
76
- # Bind the widgets to the create_plot function
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- final = pn.Row(pn.bind(create_plot,
78
- subgroup=select,
79
- date_range=date_range_slider,
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- moving_av_window=moving_av_slider))
81
 
 
 
82
 
83
- # # Combine everything in a Panel Column to create an app
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- maincol=pn.Column()
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- maincol.append(final)
 
 
 
 
 
 
 
 
 
 
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  maincol.append(select)
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- maincol.append(date_range_slider)
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- maincol.append(moving_av_slider)
 
 
 
 
 
89
  template.main.append(maincol)
90
 
91
- # # set the app to be servable
92
- template.serverable(title='SI649 Altair3')
 
1
+ # load up the libraries
 
2
  import panel as pn
 
 
3
  import pandas as pd
4
  import altair as alt
 
 
 
5
  from vega_datasets import data
 
 
 
 
 
 
 
6
 
7
+ # we want to use bootstrap/template, tell Panel to load up what we need
 
 
 
8
  pn.extension(design='bootstrap')
9
+
10
+ # we want to use vega, tell Panel to load up what we need
11
  pn.extension('vega')
12
 
13
+ # create a basic template using bootstrap
14
  template = pn.template.BootstrapTemplate(
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+ title='SI649 Walkthrough',
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  )
17
 
18
+ # the main column will hold our key content
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+ maincol = pn.Column()
20
 
21
+ # add some markdown to the main column
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+ maincol.append("# Markdown Title")
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+ maincol.append("I can format in cool ways. Like **bold** or *italics* or ***both*** or ~~strikethrough~~ or `code` or [links](https://panel.holoviz.org)")
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+ maincol.append("I am writing a link [to the streamlit documentation page](https://docs.streamlit.io/en/stable/api.html)")
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+ maincol.append('![alt text](https://upload.wikimedia.org/wikipedia/commons/thumb/3/3e/Irises-Vincent_van_Gogh.jpg/314px-Irises-Vincent_van_Gogh.jpg)')
26
 
27
+ # load up a dataframe and show it in the main column
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+ cars_url = "https://raw.githubusercontent.com/altair-viz/vega_datasets/master/vega_datasets/_data/cars.json"
29
+ cars = pd.read_json(cars_url)
30
+ temps = data.seattle_weather()
 
31
 
32
+ maincol.append(temps.head(10))
 
 
 
 
33
 
34
+ # create a basic chart
35
+ hp_mpg = alt.Chart(cars).mark_circle(size=80).encode(
36
+ x='Horsepower:Q',
37
+ y='Miles_per_Gallon:Q',
38
+ color='Origin:N'
39
+ )
40
 
41
+ # dispaly it in the main column
42
+ # maincol.append(hp_mpg)
43
 
44
+ # create a basic slider
45
+ simpleslider = pn.widgets.IntSlider(name='Simple Slider', start=0, end=100, value=0)
46
 
47
+ # generate text based on slider value
48
+ def square(x):
49
+ return f'{x} squared is {x**2}'
50
+
51
+
52
+ # bind the slider to the function and hold the output in a row
53
+ row = pn.Column(pn.bind(square,simpleslider))
54
 
55
+ # add both slider and row
56
+ maincol.append(simpleslider)
57
+ maincol.append(row)
58
 
59
+ # variable to track state of visualization
60
+ flip = False
61
 
62
+ # function to either return the vis or a message
63
+ def makeChartVisible(val):
64
+ global flip # grab the variable outside the function
65
+ if (flip == True):
66
+ flip = not flip # flip to False
67
+ return pn.pane.Vega(hp_mpg) # return the vis
68
+ else:
69
+ flip = not flip # flip to true and return text
70
+ return pn.panel("Click the button to see the chart")
71
+
72
+ # add a button and then create the binding
73
+ btn = pn.widgets.Button(name='Click me')
74
+ row = pn.Row(pn.bind(makeChartVisible, btn))
75
+
76
+ # add button and new row to main column
77
+ maincol.append(btn)
78
+ maincol.append(row)
79
+
80
+ # create a base chart
81
+ basechart = alt.Chart(cars).mark_circle(size=80,opacity=0.5).encode(
82
+ x='Horsepower:Q',
83
+ y='Acceleration:Q',
84
+ color="Origin:N"
85
+ )
86
 
87
+ # create something to hold the base chart
88
+ currentoption = pn.panel(basechart)
 
 
 
89
 
90
+ # create a selection widget
91
+ select = pn.widgets.Select(name='Select', options=['Horsepower','Acceleration','Miles_per_Gallon'])
92
 
93
+ # create a function to modify the basechart that is being
94
+ # held in currentoption
95
+ def changeOption(val):
96
+ # grab what's there now
97
+ chrt = currentoption.object
98
+ # change the encoding based on val
99
+ chrt = chrt.encode(
100
+ y=val+":Q"
101
+ )
102
+ # replace old chart in currentoption with new one
103
+ currentoption.object = chrt
104
+
105
+ # append the selection
106
  maincol.append(select)
107
+ # append the binding (in thise case nothing is being returned by changeOption, so...)
108
+ chartchange = pn.Row(pn.bind(changeOption, select))
109
+ # ... we need to also add the chart
110
+ maincol.append(chartchange)
111
+ maincol.append(currentoption)
112
+
113
+ # add the main column to the template
114
  template.main.append(maincol)
115
 
116
+ # Indicate that the template object is the "application" and serve it
117
+ template.servable(title="SI649 Walkthrough")