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‎README.md

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```python
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<DF> = <DF>.set_index(column_key) # Replaces row keys with values from a column.
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<DF> = <DF>.reset_index() # Moves row keys to their own column.
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<DF> = <DF>.transpose() # Rotates the table.
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<DF> = <DF>.melt(id_vars=column_key/s) # Melts on columns.
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<DF> = <DF>.filter('<regex>', axis=1) # Only keeps columns whose key matches the regex.
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<DF> = <DF>.melt(id_vars=column_key/s) # Convers DF from wide to long format.
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```
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#### Merge, Join, Concat:
@@ -3387,12 +3387,12 @@ def scrape_data():
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covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv',
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usecols=['date', 'total_cases'])
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covid = covid.groupby('date').sum()
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dow, gold, btc = [scrape_yahoo(id_) for id_ in ('^DJI', 'GC=F', 'BTC-USD')]
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dow.name, gold.name, btc.name = 'Dow Jones', 'Gold', 'Bitcoin'
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return covid, dow, gold, btc
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dow, gold, bitcoin = [scrape_yahoo(id_) for id_ in ('^DJI', 'GC=F', 'BTC-USD')]
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dow.name, gold.name, bitcoin.name = 'Dow Jones', 'Gold', 'Bitcoin'
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return covid, dow, gold, bitcoin
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def wrangle_data(covid, dow, gold, btc):
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df = pandas.concat([covid, dow, gold, btc], axis=1)
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def wrangle_data(covid, dow, gold, bitcoin):
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df = pandas.concat([covid, dow, gold, bitcoin], axis=1)
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df = df.loc['2020-02-23':].iloc[:-2]
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df = df.interpolate()
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df.iloc[:, 1:] = df.rolling(10, min_periods=1, center=True).mean().iloc[:, 1:]

‎index.html

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</code></pre>
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<pre><code class="python language-python hljs">&lt;DF&gt; = &lt;DF&gt;.set_index(column_key) <span class="hljs-comment"># Replaces row keys with values from a column.</span>
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&lt;DF&gt; = &lt;DF&gt;.reset_index() <span class="hljs-comment"># Moves row keys to their own column.</span>
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&lt;DF&gt; = &lt;DF&gt;.transpose() <span class="hljs-comment"># Rotates the table.</span>
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&lt;DF&gt; = &lt;DF&gt;.melt(id_vars=column_key/s) <span class="hljs-comment"># Melts on columns.</span>
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&lt;DF&gt; = &lt;DF&gt;.filter(<span class="hljs-string">'&lt;regex&gt;'</span>, axis=<span class="hljs-number">1</span>) <span class="hljs-comment"># Only keeps columns whose key matches the regex.</span>
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&lt;DF&gt; = &lt;DF&gt;.melt(id_vars=column_key/s) <span class="hljs-comment"># Convers DF from wide to long format.</span>
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</code></pre>
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<div><h4 id="mergejoinconcat">Merge, Join, Concat:</h4><pre><code class="python language-python hljs"><span class="hljs-meta">&gt;&gt;&gt; </span>l = DataFrame([[<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], [<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]], index=[<span class="hljs-string">'a'</span>, <span class="hljs-string">'b'</span>], columns=[<span class="hljs-string">'x'</span>, <span class="hljs-string">'y'</span>])
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x y
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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">'date'</span>, <span class="hljs-string">'total_cases'</span>])
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covid = covid.groupby(<span class="hljs-string">'date'</span>).sum()
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dow, gold, btc = [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>)]
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dow.name, gold.name, btc.name = <span class="hljs-string">'Dow Jones'</span>, <span class="hljs-string">'Gold'</span>, <span class="hljs-string">'Bitcoin'</span>
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<span class="hljs-keyword">return</span> covid, dow, gold, btc
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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>)]
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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>
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<span class="hljs-keyword">return</span> covid, dow, gold, bitcoin
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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, dow, gold, btc)</span>:</span>
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df = pandas.concat([covid, dow, gold, btc], axis=<span class="hljs-number">1</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, dow, gold, bitcoin)</span>:</span>
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df = pandas.concat([covid, dow, gold, bitcoin], axis=<span class="hljs-number">1</span>)
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df = df.loc[<span class="hljs-string">'2020-02-23'</span>:].iloc[:<span class="hljs-number">-2</span>]
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df = df.interpolate()
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df.iloc[:, <span class="hljs-number">1</span>:] = df.rolling(<span class="hljs-number">10</span>, min_periods=<span class="hljs-number">1</span>, center=<span class="hljs-keyword">True</span>).mean().iloc[:, <span class="hljs-number">1</span>:]

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