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Plotly
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‎README.md

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@@ -3428,7 +3428,7 @@ import pandas as pd, plotly.express as ex
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#### Displays a line chart of total coronavirus deaths per million grouped by continent:
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![Covid Deaths](web/covid_deaths.png)
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<div id="2a950764-39fc-416d-97fe-0a6226a3095f" class="plotly-graph-div" style="height:321px; width:100%;"></div>
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<div id="2a950764-39fc-416d-97fe-0a6226a3095f" class="plotly-graph-div" style="height:312px; width:914px;"></div>
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```python
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covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv',
@@ -3447,25 +3447,26 @@ ex.line(df, x='Date', y='Total Deaths per Million', color='Continent').show()
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#### Displays a multi-axis line chart of total coronavirus cases and changes in prices of Bitcoin, Dow Jones and gold:
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![Covid Cases](web/covid_cases.png)
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<div id="e23ccacc-a456-478b-b467-7282a2165921" class="plotly-graph-div" style="height:315px; width:100%;"></div>
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<div id="e23ccacc-a456-478b-b467-7282a2165921" class="plotly-graph-div" style="height:287px; width:935px;"></div>
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```python
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import pandas as pd, plotly.graph_objects as go
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def main():
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display_data(wrangle_data(*scrape_data()))
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covid, bitcoin, gold, dow = scrape_data()
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display_data(wrangle_data(covid, bitcoin, gold, dow))
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def scrape_data():
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def scrape_covid():
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def get_covid_cases():
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url = 'https://covid.ourworldindata.org/data/owid-covid-data.csv'
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df = pd.read_csv(url, usecols=['location', 'date', 'total_cases'])
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return df[df.location == 'World'].set_index('date').total_cases
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def scrape_yahoo(slug):
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url = (f'https://query1.finance.yahoo.com/v7/finance/download/{slug}?'
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def get_ticker(symbol):
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url = (f'https://query1.finance.yahoo.com/v7/finance/download/{symbol}?'
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'period1=1579651200&period2=9999999999&interval=1d&events=history')
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df = pd.read_csv(url, usecols=['Date', 'Close'])
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return df.set_index('Date').Close
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out = scrape_covid(), scrape_yahoo('BTC-USD'), scrape_yahoo('GC=F'), scrape_yahoo('^DJI')
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out = get_covid_cases(), get_ticker('BTC-USD'), get_ticker('GC=F'), get_ticker('^DJI')
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return map(pd.Series.rename, out, ['Total Cases', 'Bitcoin', 'Gold', 'Dow Jones'])
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def wrangle_data(covid, bitcoin, gold, dow):
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figure.update_layout(
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yaxis1=dict(title='Total Cases', rangemode='tozero'),
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yaxis2=dict(title='%', rangemode='tozero', overlaying='y', side='right'),
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legend=dict(x=1.1),
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height=450
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legend=dict(x=1.08),
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width=944,
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height=423
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)
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figure.show()
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‎index.html

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<body>
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<header>
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<aside>November 5, 2023</aside>
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<aside>November 12, 2023</aside>
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<a href="https://gto76.github.io" rel="author">Jure Šorn</a>
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</header>
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@@ -2786,7 +2786,7 @@ <h3 id="format-2">Format</h3><div><h4 id="forstandardtypesizesandmanualalignment
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&lt;Figure&gt;.write_html/json/image(<span class="hljs-string">'&lt;path&gt;'</span>) <span class="hljs-comment"># Also &lt;Figure&gt;.show().</span>
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</code></pre></div>
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<div><h4 id="displaysalinechartoftotalcoronavirusdeathspermilliongroupedbycontinent">Displays a line chart of total coronavirus deaths per million grouped by continent:</h4><p></p><div id="2a950764-39fc-416d-97fe-0a6226a3095f" class="plotly-graph-div" style="height:321px; width:100%;"></div><pre><code class="python language-python hljs">covid = pd.read_csv(<span class="hljs-string">'https://covid.ourworldindata.org/data/owid-covid-data.csv'</span>,
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<div><h4 id="displaysalinechartoftotalcoronavirusdeathspermilliongroupedbycontinent">Displays a line chart of total coronavirus deaths per million grouped by continent:</h4><p></p><div id="2a950764-39fc-416d-97fe-0a6226a3095f" class="plotly-graph-div" style="height:312px; width:914px;"></div><pre><code class="python language-python hljs">covid = pd.read_csv(<span class="hljs-string">'https://covid.ourworldindata.org/data/owid-covid-data.csv'</span>,
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usecols=[<span class="hljs-string">'iso_code'</span>, <span class="hljs-string">'date'</span>, <span class="hljs-string">'total_deaths'</span>, <span class="hljs-string">'population'</span>])
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continents = pd.read_csv(<span class="hljs-string">'https://gist.githubusercontent.com/stevewithington/20a69c0b6d2ff'</span>
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<span class="hljs-string">'846ea5d35e5fc47f26c/raw/country-and-continent-codes-list-csv.csv'</span>,
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<div><h4 id="displaysamultiaxislinechartoftotalcoronaviruscasesandchangesinpricesofbitcoindowjonesandgold">Displays a multi-axis line chart of total coronavirus cases and changes in prices of Bitcoin, Dow Jones and gold:</h4><p></p><div id="e23ccacc-a456-478b-b467-7282a2165921" class="plotly-graph-div" style="height:315px; width:100%;"></div><pre><code class="python language-python hljs"><span class="hljs-keyword">import</span> pandas <span class="hljs-keyword">as</span> pd, plotly.graph_objects <span class="hljs-keyword">as</span> go
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<div><h4 id="displaysamultiaxislinechartoftotalcoronaviruscasesandchangesinpricesofbitcoindowjonesandgold">Displays a multi-axis line chart of total coronavirus cases and changes in prices of Bitcoin, Dow Jones and gold:</h4><p></p><div id="e23ccacc-a456-478b-b467-7282a2165921" class="plotly-graph-div" style="height:287px; width:935px;"></div><pre><code class="python language-python hljs"><span class="hljs-keyword">import</span> pandas <span class="hljs-keyword">as</span> pd, plotly.graph_objects <span class="hljs-keyword">as</span> go
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<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">main</span><span class="hljs-params">()</span>:</span>
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display_data(wrangle_data(*scrape_data()))
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covid, bitcoin, gold, dow = scrape_data()
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display_data(wrangle_data(covid, bitcoin, gold, dow))
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<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">scrape_data</span><span class="hljs-params">()</span>:</span>
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<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">scrape_covid</span><span class="hljs-params">()</span>:</span>
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<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">get_covid_cases</span><span class="hljs-params">()</span>:</span>
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url = <span class="hljs-string">'https://covid.ourworldindata.org/data/owid-covid-data.csv'</span>
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df = pd.read_csv(url, usecols=[<span class="hljs-string">'location'</span>, <span class="hljs-string">'date'</span>, <span class="hljs-string">'total_cases'</span>])
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<span class="hljs-keyword">return</span> df[df.location == <span class="hljs-string">'World'</span>].set_index(<span class="hljs-string">'date'</span>).total_cases
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<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">scrape_yahoo</span><span class="hljs-params">(slug)</span>:</span>
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url = (<span class="hljs-string">f'https://query1.finance.yahoo.com/v7/finance/download/<span class="hljs-subst">{slug}</span>?'</span>
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<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">get_ticker</span><span class="hljs-params">(symbol)</span>:</span>
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url = (<span class="hljs-string">f'https://query1.finance.yahoo.com/v7/finance/download/<span class="hljs-subst">{symbol}</span>?'</span>
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<span class="hljs-string">'period1=1579651200&amp;period2=9999999999&amp;interval=1d&amp;events=history'</span>)
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df = pd.read_csv(url, usecols=[<span class="hljs-string">'Date'</span>, <span class="hljs-string">'Close'</span>])
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<span class="hljs-keyword">return</span> df.set_index(<span class="hljs-string">'Date'</span>).Close
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out = scrape_covid(), scrape_yahoo(<span class="hljs-string">'BTC-USD'</span>), scrape_yahoo(<span class="hljs-string">'GC=F'</span>), scrape_yahoo(<span class="hljs-string">'^DJI'</span>)
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out = get_covid_cases(), get_ticker(<span class="hljs-string">'BTC-USD'</span>), get_ticker(<span class="hljs-string">'GC=F'</span>), get_ticker(<span class="hljs-string">'^DJI'</span>)
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<span class="hljs-keyword">return</span> map(pd.Series.rename, out, [<span class="hljs-string">'Total Cases'</span>, <span class="hljs-string">'Bitcoin'</span>, <span class="hljs-string">'Gold'</span>, <span class="hljs-string">'Dow Jones'</span>])
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<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">wrangle_data</span><span class="hljs-params">(covid, bitcoin, gold, dow)</span>:</span>
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figure.update_layout(
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yaxis1=dict(title=<span class="hljs-string">'Total Cases'</span>, rangemode=<span class="hljs-string">'tozero'</span>),
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yaxis2=dict(title=<span class="hljs-string">'%'</span>, rangemode=<span class="hljs-string">'tozero'</span>, overlaying=<span class="hljs-string">'y'</span>, side=<span class="hljs-string">'right'</span>),
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legend=dict(x=<span class="hljs-number">1.1</span>),
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height=<span class="hljs-number">450</span>
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legend=dict(x=<span class="hljs-number">1.08</span>),
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width=<span class="hljs-number">944</span>,
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height=<span class="hljs-number">423</span>
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)
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figure.show()
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<footer>
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<aside>November 5, 2023</aside>
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<aside>November 12, 2023</aside>
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<a href="https://gto76.github.io" rel="author">Jure Šorn</a>
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</footer>
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‎web/covid_cases.js

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"side": "right"
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},
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"legend": {
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"x": 1.1
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"x": 1.08
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},
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"margin": {
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"t": 24,

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