Browse Source

Updated plot images

pull/79/head
Jure Šorn 4 years ago
parent
commit
b632adda35
7 changed files with 73 additions and 44 deletions
  1. 2
      README.md
  2. 2
      index.html
  3. 48
      web/covid_cases.js
  4. BIN
      web/covid_cases.png
  5. 44
      web/covid_deaths.js
  6. BIN
      web/covid_deaths.png
  7. 21
      web/update_plots.py

2
README.md

@ -3367,7 +3367,7 @@ continents = pd.read_csv('https://datahub.io/JohnSnowLabs/country-and-continent-
df = pd.merge(covid, continents, left_on='iso_code', right_on='Three_Letter_Country_Code')
df = df.groupby(['Continent_Name', 'date']).sum().reset_index()
df['Total Deaths per Million'] = df.total_deaths * 1e6 / df.population
df = df[('2020-03-14' < df.date) & (df.date < '2020-10-22')]
df = df[('2020-03-14' < df.date) & (df.date < '2020-10-23')]
df = df.rename({'date': 'Date', 'Continent_Name': 'Continent'}, axis='columns')
line(df, x='Date', y='Total Deaths per Million', color='Continent').show()
```

2
index.html

@ -2858,7 +2858,7 @@ continents = pd.read_csv(<span class="hljs-string">'https://datahub.io/JohnSnowL
df = pd.merge(covid, continents, left_on=<span class="hljs-string">'iso_code'</span>, right_on=<span class="hljs-string">'Three_Letter_Country_Code'</span>)
df = df.groupby([<span class="hljs-string">'Continent_Name'</span>, <span class="hljs-string">'date'</span>]).sum().reset_index()
df[<span class="hljs-string">'Total Deaths per Million'</span>] = df.total_deaths * <span class="hljs-number">1e6</span> / df.population
df = df[(<span class="hljs-string">'2020-03-14'</span> &lt; df.date) &amp; (df.date &lt; <span class="hljs-string">'2020-10-22'</span>)]
df = df[(<span class="hljs-string">'2020-03-14'</span> &lt; df.date) &amp; (df.date &lt; <span class="hljs-string">'2020-10-23'</span>)]
df = df.rename({<span class="hljs-string">'date'</span>: <span class="hljs-string">'Date'</span>, <span class="hljs-string">'Continent_Name'</span>: <span class="hljs-string">'Continent'</span>}, axis=<span class="hljs-string">'columns'</span>)
line(df, x=<span class="hljs-string">'Date'</span>, y=<span class="hljs-string">'Total Deaths per Million'</span>, color=<span class="hljs-string">'Continent'</span>).show()
</code></pre></div>

48
web/covid_cases.js

@ -252,7 +252,8 @@ if (document.getElementById("e23ccacc-a456-478b-b467-7282a2165921")) {
"2020-10-19",
"2020-10-20",
"2020-10-21",
"2020-10-22"
"2020-10-22",
"2020-10-23"
],
"y": [
100.0,
@ -496,8 +497,9 @@ if (document.getElementById("e23ccacc-a456-478b-b467-7282a2165921")) {
100.94579531386498,
100.82351279089583,
100.76013021633324,
100.70921780571318,
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100.70378136188316,
100.60235832660891,
100.53639551861964
],
"yaxis": "y2"
},
@ -747,7 +749,8 @@ if (document.getElementById("e23ccacc-a456-478b-b467-7282a2165921")) {
"2020-10-19",
"2020-10-20",
"2020-10-21",
"2020-10-22"
"2020-10-22",
"2020-10-23"
],
"y": [
100.0,
@ -991,8 +994,9 @@ if (document.getElementById("e23ccacc-a456-478b-b467-7282a2165921")) {
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],
"yaxis": "y2"
},
@ -1242,7 +1246,8 @@ if (document.getElementById("e23ccacc-a456-478b-b467-7282a2165921")) {
"2020-10-19",
"2020-10-20",
"2020-10-21",
"2020-10-22"
"2020-10-22",
"2020-10-23"
],
"y": [
100.0,
@ -1485,9 +1490,10 @@ if (document.getElementById("e23ccacc-a456-478b-b467-7282a2165921")) {
122.35777113065551,
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],
"yaxis": "y2"
},
@ -1737,7 +1743,8 @@ if (document.getElementById("e23ccacc-a456-478b-b467-7282a2165921")) {
"2020-10-19",
"2020-10-20",
"2020-10-21",
"2020-10-22"
"2020-10-22",
"2020-10-23"
],
"y": [
157636.0,
@ -1974,15 +1981,16 @@ if (document.getElementById("e23ccacc-a456-478b-b467-7282a2165921")) {
74653792.0,
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],
"yaxis": "y"
}

BIN
web/covid_cases.png

Before After
Width: 1401  |  Height: 619  |  Size: 99 KiB Width: 960  |  Height: 315  |  Size: 55 KiB

44
web/covid_deaths.js

@ -238,7 +238,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
"2020-10-18",
"2020-10-19",
"2020-10-20",
"2020-10-21"
"2020-10-21",
"2020-10-22"
],
"xaxis": "x",
"y": [
@ -462,7 +463,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
29.530605941746504,
29.670218201217267,
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30.024848272065466,
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],
"yaxis": "y"
},
@ -698,7 +700,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
"2020-10-18",
"2020-10-19",
"2020-10-20",
"2020-10-21"
"2020-10-21",
"2020-10-22"
],
"xaxis": "x",
"y": [
@ -922,7 +925,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
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@ -1158,7 +1162,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
"2020-10-18",
"2020-10-19",
"2020-10-20",
"2020-10-21"
"2020-10-21",
"2020-10-22"
],
"xaxis": "x",
"y": [
@ -1382,7 +1387,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
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"yaxis": "y"
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@ -1618,7 +1624,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
"2020-10-18",
"2020-10-19",
"2020-10-20",
"2020-10-21"
"2020-10-21",
"2020-10-22"
],
"xaxis": "x",
"y": [
@ -1842,7 +1849,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
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"yaxis": "y"
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@ -2078,7 +2086,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
"2020-10-18",
"2020-10-19",
"2020-10-20",
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"2020-10-21",
"2020-10-22"
],
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@ -2298,11 +2307,12 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
24.75687479369271,
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],
"yaxis": "y"
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@ -2538,7 +2548,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
"2020-10-18",
"2020-10-19",
"2020-10-20",
"2020-10-21"
"2020-10-21",
"2020-10-22"
],
"xaxis": "x",
"y": [
@ -2762,7 +2773,8 @@ if (document.getElementById("2a950764-39fc-416d-97fe-0a6226a3095f")) {
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BIN
web/covid_deaths.png

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Width: 1395  |  Height: 645  |  Size: 102 KiB Width: 960  |  Height: 340  |  Size: 45 KiB

21
web/update_plots.py

@ -12,18 +12,18 @@ import re
def main():
# print('Updating covid deaths...')
# update_covid_deaths()
print('Updating covid deaths...')
update_covid_deaths()
print('Updating covid cases...')
update_confirmed_cases()
def update_covid_deaths():
def update_readme(date_treshold):
lines = read_file('../README.md')
lines = read_file(Path('..') / 'README.md')
out = [re.sub("df.date < '\d{4}-\d{2}-\d{2}'", f"df.date < '{date_treshold}'", line)
for line in lines]
write_to_file('../README.md', out)
write_to_file(Path('..') / 'README.md', out)
covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv',
usecols=['iso_code', 'date', 'total_deaths', 'population'])
continents = pd.read_csv('https://datahub.io/JohnSnowLabs/country-and-continent-codes-' + \
@ -39,6 +39,7 @@ def update_covid_deaths():
f.update_layout(margin=dict(t=24, b=0), paper_bgcolor='rgba(0, 0, 0, 0)')
update_file('covid_deaths.js', f)
update_readme(date_treshold)
write_to_png_file('covid_deaths.png', f, width=960, height=340)
def update_confirmed_cases():
@ -46,6 +47,7 @@ def update_confirmed_cases():
df = wrangle_data(*scrape_data())
f = get_figure(df)
update_file('covid_cases.js', f)
write_to_png_file('covid_cases.png', f, width=960, height=315)
def scrape_data():
def scrape_yahoo(id_):
@ -99,14 +101,21 @@ def update_file(filename, figure):
#
def read_file(filename):
with open(filename, encoding='utf-8') as file:
p = Path(__file__).resolve().parent / filename
with open(p, encoding='utf-8') as file:
return file.readlines()
def write_to_file(filename, lines):
with open(filename, 'w', encoding='utf-8') as file:
p = Path(__file__).resolve().parent / filename
with open(p, 'w', encoding='utf-8') as file:
file.writelines(lines)
def write_to_png_file(filename, figure, width, height):
p = Path(__file__).resolve().parent / filename
figure.write_image(str(p), width=width, height=height)
if __name__ == '__main__':
main()
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