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Fixed confirmed covid cases plot

pull/79/head
Jure Šorn 4 years ago
parent
22b9d3c104
commit
3ea47faa63
7 changed files with 353 additions and 293 deletions
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  1. 6
      README.md
  2. 6
      index.html
  3. 542
      web/covid_cases.js
  4. BIN
      web/covid_cases.png
  5. 88
      web/covid_deaths.js
  6. BIN
      web/covid_deaths.png
  7. 4
      web/update_plots.py

6
README.md
View File

@ -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 < '2020-10-23')]
df = df[('2020-03-14' < df.date) & (df.date < '2020-10-26')]
df = df.rename({'date': 'Date', 'Continent_Name': 'Continent'}, axis='columns')
line(df, x='Date', y='Total Deaths per Million', color='Continent').show()
```
@ -3392,8 +3392,8 @@ def scrape_data():
url = f'{BASE_URL}{id_}?period1=1579651200&period2={now}&interval=1d&events=history'
return pd.read_csv(url, usecols=['Date', 'Close']).set_index('Date').Close
covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv',
usecols=['date', 'total_cases'])
covid = covid.groupby('date').sum()
usecols=['location', 'date', 'total_cases'])
covid = covid[covid.location == 'World'].set_index('date').total_cases
dow, gold, bitcoin = [scrape_yahoo(id_) for id_ in ('^DJI', 'GC=F', 'BTC-USD')]
dow.name, gold.name, bitcoin.name = 'Dow Jones', 'Gold', 'Bitcoin'
return covid, dow, gold, bitcoin

6
index.html
View File

@ -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">'2020-10-23'</span>)]
df = df[(<span class="hljs-string">'2020-03-14'</span> &lt; df.date) &amp; (df.date &lt; <span class="hljs-string">'2020-10-26'</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>
@ -2879,8 +2879,8 @@ line(df, x=<span class="hljs-string">'Date'</span>, y=<span class="hljs-string">
url = <span class="hljs-string">f'<span class="hljs-subst">{BASE_URL}</span><span class="hljs-subst">{id_}</span>?period1=1579651200&amp;period2=<span class="hljs-subst">{now}</span>&amp;interval=1d&amp;events=history'</span>
<span class="hljs-keyword">return</span> pd.read_csv(url, usecols=[<span class="hljs-string">'Date'</span>, <span class="hljs-string">'Close'</span>]).set_index(<span class="hljs-string">'Date'</span>).Close
covid = pd.read_csv(<span class="hljs-string">'https://covid.ourworldindata.org/data/owid-covid-data.csv'</span>,
usecols=[<span class="hljs-string">'date'</span>, <span class="hljs-string">'total_cases'</span>])
covid = covid.groupby(<span class="hljs-string">'date'</span>).sum()
usecols=[<span class="hljs-string">'location'</span>, <span class="hljs-string">'date'</span>, <span class="hljs-string">'total_cases'</span>])
covid = covid[covid.location == <span class="hljs-string">'World'</span>].set_index(<span class="hljs-string">'date'</span>).total_cases
dow, gold, bitcoin = [scrape_yahoo(id_) <span class="hljs-keyword">for</span> id_ <span class="hljs-keyword">in</span> (<span class="hljs-string">'^DJI'</span>, <span class="hljs-string">'GC=F'</span>, <span class="hljs-string">'BTC-USD'</span>)]
dow.name, gold.name, bitcoin.name = <span class="hljs-string">'Dow Jones'</span>, <span class="hljs-string">'Gold'</span>, <span class="hljs-string">'Bitcoin'</span>
<span class="hljs-keyword">return</span> covid, dow, gold, bitcoin

542
web/covid_cases.js
View File

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}

BIN
web/covid_cases.png
View File

Before After
Width: 960  |  Height: 315  |  Size: 55 KiB Width: 960  |  Height: 315  |  Size: 55 KiB

88
web/covid_deaths.js
View File

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BIN
web/covid_deaths.png
View File

Before After
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4
web/update_plots.py
View File

@ -56,8 +56,8 @@ def update_confirmed_cases():
url = f'{BASE_URL}{id_}?period1=1579651200&period2={now}&interval=1d&events=history'
return pd.read_csv(url, usecols=['Date', 'Close']).set_index('Date').Close
covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv',
usecols=['date', 'total_cases'])
covid = covid.groupby('date').sum()
usecols=['location', 'date', 'total_cases'])
covid = covid[covid.location == 'World'].set_index('date').total_cases
dow, gold, bitcoin = [scrape_yahoo(id_) for id_ in ('^DJI', 'GC=F', 'BTC-USD')]
dow.name, gold.name, bitcoin.name = 'Dow Jones', 'Gold', 'Bitcoin'
return covid, dow, gold, bitcoin

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