Pandas

4 years ago · 415e537014
2 changed files with 183 additions and 89 deletions
--- a/README.md
+++ b/README.md
@ -3076,7 +3076,7 @@ from pandas import Series, DataFrame
 **Ordered dictionary with a name.**
 ```python
 >>> Series([1, 2], index=['x', 'y'], name='a')
 >>> sr = Series([1, 2], index=['x', 'y'], name='a')
 x    1
 y    2
 Name: a, dtype: int64
@ -3110,22 +3110,37 @@ Name: a, dtype: int64
 <Sr> = <Sr>.combine_first(<Sr>)               # Adds items that are not yet present (extends).
 ```
 #### Operations:
 #### Aggregations:
 ```python
 <el> = <Sr>.sum/max/mean/idxmax/all()
 <el> = <agg_func>(<Sr>)
 <el> = <Sr>.apply/agg(<agg_func>)             # Apply can only accept strings.
 ```
 ```python
 +-------------+--------+-----------+---------------+
 |             |  'sum' |  ['sum']  |  {'s': 'sum'} |
 +-------------+--------+-----------+---------------+
 | sr.apply(…) |        |           |               |
 | sr.agg(…)   |    3   |   sum 3   |      s  3     |
 |             |        |           |               |
 +-------------+--------+-----------+---------------+
 ```
 #### Transformations:
 ```python
 <Sr> = <Sr>.diff/cumsum/rank/pct_change()     # …/fillna/ffill/interpolate()
 <el> = <Sr>.apply/agg(<agg_func>)
 <Sr> = <Sr>.apply/agg/transform(<trans_func>)
 ```
 ```python
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 |             |    'sum'   |  ['sum']  | {'s': 'sum'} | 'rank' |  ['rank']   | {'r': 'rank'} |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | sr.apply(…) |            |           |              |        |      rank   |               |
 | sr.agg(…)   |      3     |   sum 3   |     s  3     |  x  1  |   x     1   |    r  x  1    |
 |             |            |           |              |  y  2  |   y     2   |       y  2    |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 +-------------+--------+-----------+---------------+
 |             | 'rank' | ['rank']  | {'r': 'rank'} |
 +-------------+--------+-----------+---------------+
 | sr.apply(…) |        |     rank  |               |
 | sr.agg(…)   |  x  1  |  x     1  |    r  x  1    |
 | sr.trans(…) |  y  2  |  y     2  |       y  2    |
 +-------------+--------+-----------+---------------+
 ```
 ### DataFrame
@ -3168,27 +3183,44 @@ b  3  4
 <DF>    = <DF>.melt(id_vars=column_key/s)     # Melts on columns.
 ```
 #### Operations:
 ```python
 <Sr>    = <DF>.sum/max/mean/idxmax/all()
 <DF>    = <DF>.diff/cumsum/rank()             # …/pct_change/fillna/ffill/interpolate()
 <Sr>    = <DF>.apply/agg/transform(<agg_func>)
 <DF>    = <DF>.diff/cumsum/rank()             # …/pct_change/fillna/ffill/interpolate()
 <DF>    = <DF>.apply/agg/transform(<trans_func>)
 <DF>    = <DF>.applymap(<func>)               # Apply a function to a Dataframe elementwise.
 ```
 * **All operations operate on columns by default. Use `'axis=1'` parameter to process the rows instead.** 
 #### Apply, Aggregate, Transform:
 ```python
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 |             |    'sum'   |  ['sum']  | {'x': 'sum'} | 'rank' |  ['rank']   | {'x': 'rank'} |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | df.apply(…) |            |      x y  |              |    x y |      x    y |        x      |
 | df.agg(…)   |    x  4    |  sum 4 6  |     x  4     | a  1 1 |   rank rank |     a  1      |
 | df.trans(…) |    y  6    |           |              | b  2 2 | a    1    1 |     b  2      |
 |             |            |           |              |        | b    2    2 |               |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 >>> df = DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y'])
   x  y
 a  1  2
 b  3  4
 ```
 * **Transform doesen't work with `['sum']` and `{'x': 'sum'}`.**
 ```python
 +-------------+---------------+---------------+---------------+
 |             |     'sum'     |    ['sum']    | {'x': 'sum'}  |
 +-------------+---------------+---------------+---------------+
 | df.apply(…) |               |        x y    |               |
 | df.agg(…)   |     x  4      |    sum 4 6    |     x  4      |
 | df.trans(…) |     y  6      |               |               |
 +-------------+---------------+---------------+---------------+
 ```
 ```python
 +-------------+---------------+---------------+---------------+
 |             |    'rank'     |   ['rank']    | {'x': 'rank'} |
 +-------------+---------------+---------------+---------------+
 | df.apply(…) |       x  y    |       x    y  |        x      |
 | df.agg(…)   |    a  1  1    |    rank rank  |     a  1      |
 | df.trans(…) |    b  2  2    |  a    1    1  |     b  2      |
 |             |               |  b    2    2  |               |
 +-------------+---------------+---------------+---------------+
 ```
 * **Transform() doesen't work with `['sum']` and `{'x': 'sum'}`.**
 #### Merge, Join, Concat:
 ```python
@ -3253,34 +3285,55 @@ c  6  7
 ```
 * **Result of an operation is a dataframe with index made up of group keys. Use `'<DF>.reset_index()'` to move the index back into it's own column.**
 #### Operations:
 #### Aggregations:
 ```python
 <DF> = <GB>.sum/max/mean/idxmax/all()
 <DF> = <GB>.diff/cumsum/rank()                # …/pct_change/fillna/ffill()
 <DF> = <GB>.apply/agg/transform(<agg_func>)
 ```
 ```python
 +-------------+------------+-------------+---------------+
 |             |    'sum'   |   ['sum']   | {'x': 'sum'}  |
 +-------------+------------+-------------+---------------+
 | gb.apply(…) |    x  y  z |             |               |
 |             | z          |             |               |
 |             | 3  1  2  3 |             |               |
 |             | 6 11 13 12 |             |               |
 +-------------+------------+-------------+---------------+
 | gb.agg(…)   |     x   y  |      x   y  |         x     |
 |             | z          |    sum sum  |     z         |
 |             | 3   1   2  |  z          |     3   1     |
 |             | 6  11  13  |  3   1   2  |     6  11     |
 |             |            |  6  11  13  |               |
 +-------------+------------+-------------+---------------+
 | gb.trans(…) |     x   y  |             |               |
 |             | a   1   2  |             |               |
 |             | b  11  13  |             |               |
 |             | c  11  13  |             |               |
 +-------------+------------+-------------+---------------+
 ```
 #### Transformations:
 ```python
 <DF> = <GB>.diff/cumsum/rank()                # …/pct_change/fillna/ffill()
 <DF> = <GB>.agg/transform(<trans_func>)
 ```
 ```python
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 |             |    'sum'   |  ['sum']  | {'x': 'sum'} | 'rank' |  ['rank']   | {'x': 'rank'} |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | gb.apply(…) |    x  y  z |           |              |        |             |               |
 |             | z          |           |              |        |             |               |
 |             | 3  1  2  3 |           |              |        |             |               |
 |             | 6 11 13 12 |           |              |        |             |               |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | gb.agg(…)   |     x  y   |     x   y |        x     |    x y |      x    y |         x     |
 |             |  z         |   sum sum |     z        | a  1 1 |   rank rank |      a  1     |
 |             |  3  1  2   | z         |     3  1     | b  1 1 | a    1    1 |      b  1     |
 |             |  6 11 13   | 3   1   2 |     6 11     | c  2 2 | b    1    1 |      c  2     |
 |             |            | 6  11  13 |              |        | c    2    2 |               |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | gb.trans(…) |     x  y   |           |              |    x y |             |               |
 |             |  a  1  2   |           |              | a  1 1 |             |               |
 |             |  b 11 13   |           |              | b  1 1 |             |               |
 |             |  c 11 13   |           |              | c  1 1 |             |               |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 +-------------+------------+-------------+---------------+
 |             |   'rank'   |  ['rank']   | {'x': 'rank'} |
 +-------------+------------+-------------+---------------+
 | gb.agg(…)   |     x  y   |      x    y |        x      |
 |             |  a  1  1   |   rank rank |     a  1      |
 |             |  b  1  1   | a    1    1 |     b  1      |
 |             |  c  2  2   | b    1    1 |     c  2      |
 |             |            | c    2    2 |               |
 +-------------+------------+-------------+---------------+
 | gb.trans(…) |     x  y   |             |               |
 |             |  a  1  1   |             |               |
 |             |  b  1  1   |             |               |
 |             |  c  1  1   |             |               |
 +-------------+------------+-------------+---------------+
 ```
 ### Rolling
@ -3288,7 +3341,7 @@ c  6  7
 <Rl_S/D/G> = <Sr/DF/GB>.rolling(window_size)  # Also: `min_periods=None, center=False`.
 <Rl_S/D>   = <Rl_D/G>[column_key/s]           # Or: <Rl>.column_key
 <Sr/DF/DF> = <Rl_S/D/G>.sum/max/mean()
 <Sr/DF/DF> = <Rl_S/D/G>.apply(<func>)         # Invokes function on every window.
 <Sr/DF/DF> = <Rl_S/D/G>.apply(<agg_func>)     # Invokes function on every window.
 <Sr/DF/DF> = <Rl_S/D/G>.aggregate(<func/str>) # Invokes function on every window.
 ```
--- a/index.html
+++ b/index.html
@ -2613,7 +2613,7 @@ SIZE, MAX_SPEED = <span class="hljs-number">50</span>, P(<span class="hljs-numbe
 <span class="hljs-keyword">from</span> pandas <span class="hljs-keyword">import</span> Series, DataFrame
 </code></pre></div>
 <div><h3 id="series">Series</h3><p><strong>Ordered dictionary with a name.</strong></p><pre><code class="python language-python hljs"><span class="hljs-meta">&gt;&gt;&gt; </span>Series([<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], index=[<span class="hljs-string">'x'</span>, <span class="hljs-string">'y'</span>], name=<span class="hljs-string">'a'</span>)
 <div><h3 id="series">Series</h3><p><strong>Ordered dictionary with a name.</strong></p><pre><code class="python language-python hljs"><span class="hljs-meta">&gt;&gt;&gt; </span>sr = Series([<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], index=[<span class="hljs-string">'x'</span>, <span class="hljs-string">'y'</span>], name=<span class="hljs-string">'a'</span>)
 x    <span class="hljs-number">1</span>
 y    <span class="hljs-number">2</span>
 Name: a, dtype: int64
@ -2638,19 +2638,30 @@ Name: a, dtype: int64
 <pre><code class="python language-python hljs">&lt;Sr&gt; = &lt;Sr&gt;.append(&lt;Sr&gt;)                      <span class="hljs-comment"># Or: pd.concat(&lt;coll_of_Sr&gt;)</span>
 &lt;Sr&gt; = &lt;Sr&gt;.combine_first(&lt;Sr&gt;)               <span class="hljs-comment"># Adds items that are not yet present (extends).</span>
 </code></pre>
 <div><h4 id="operations">Operations:</h4><pre><code class="python language-python hljs">&lt;el&gt; = &lt;Sr&gt;.sum/max/mean/idxmax/all()
 &lt;Sr&gt; = &lt;Sr&gt;.diff/cumsum/rank/pct_change()     <span class="hljs-comment"># …/fillna/ffill/interpolate()</span>
 &lt;el&gt; = &lt;Sr&gt;.apply/agg(&lt;agg_func&gt;)
 <div><h4 id="aggregations">Aggregations:</h4><pre><code class="python language-python hljs">&lt;el&gt; = &lt;Sr&gt;.sum/max/mean/idxmax/all()
 &lt;el&gt; = &lt;agg_func&gt;(&lt;Sr&gt;)
 &lt;el&gt; = &lt;Sr&gt;.apply/agg(&lt;agg_func&gt;)             <span class="hljs-comment"># Apply can only accept strings.</span>
 </code></pre></div>
 <pre><code class="python language-python hljs">+-------------+--------+-----------+---------------+
 |             |  <span class="hljs-string">'sum'</span> |  [<span class="hljs-string">'sum'</span>]  |  {<span class="hljs-string">'s'</span>: <span class="hljs-string">'sum'</span>} |
 +-------------+--------+-----------+---------------+
 | sr.apply(…) |        |           |               |
 | sr.agg(…)   |    <span class="hljs-number">3</span>   |   sum <span class="hljs-number">3</span>   |      s  <span class="hljs-number">3</span>     |
 |             |        |           |               |
 +-------------+--------+-----------+---------------+
 </code></pre>
 <div><h4 id="transformations">Transformations:</h4><pre><code class="python language-python hljs">&lt;Sr&gt; = &lt;Sr&gt;.diff/cumsum/rank/pct_change()     <span class="hljs-comment"># …/fillna/ffill/interpolate()</span>
 &lt;Sr&gt; = &lt;Sr&gt;.apply/agg/transform(&lt;trans_func&gt;)
 </code></pre></div>
 <pre><code class="python language-python hljs">+-------------+------------+-----------+--------------+--------+-------------+---------------+
 |             |    <span class="hljs-string">'sum'</span>   |  [<span class="hljs-string">'sum'</span>]  | {<span class="hljs-string">'s'</span>: <span class="hljs-string">'sum'</span>} | <span class="hljs-string">'rank'</span> |  [<span class="hljs-string">'rank'</span>]   | {<span class="hljs-string">'r'</span>: <span class="hljs-string">'rank'</span>} |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | sr.apply(…) |            |           |              |        |      rank   |               |
 | sr.agg(…)   |      <span class="hljs-number">3</span>     |   sum <span class="hljs-number">3</span>   |     s  <span class="hljs-number">3</span>     |  x  <span class="hljs-number">1</span>  |   x     <span class="hljs-number">1</span>   |    r  x  <span class="hljs-number">1</span>    |
 |             |            |           |              |  y  <span class="hljs-number">2</span>  |   y     <span class="hljs-number">2</span>   |       y  <span class="hljs-number">2</span>    |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 <pre><code class="python language-python hljs">+-------------+--------+-----------+---------------+
 |             | <span class="hljs-string">'rank'</span> | [<span class="hljs-string">'rank'</span>]  | {<span class="hljs-string">'r'</span>: <span class="hljs-string">'rank'</span>} |
 +-------------+--------+-----------+---------------+
 | sr.apply(…) |        |     rank  |               |
 | sr.agg(…)   |  x  <span class="hljs-number">1</span>  |  x     <span class="hljs-number">1</span>  |    r  x  <span class="hljs-number">1</span>    |
 | sr.trans(…) |  y  <span class="hljs-number">2</span>  |  y     <span class="hljs-number">2</span>  |       y  <span class="hljs-number">2</span>    |
 +-------------+--------+-----------+---------------+
 </code></pre>
 <div><h3 id="dataframe">DataFrame</h3><p><strong>Table with labeled rows and columns.</strong></p><pre><code class="python language-python hljs"><span class="hljs-meta">&gt;&gt;&gt; </span>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>])
   x  y
@ -2679,27 +2690,40 @@ b  <span class="hljs-number">3</span>  <span class="hljs-number">4</span>
 &lt;DF&gt;    = &lt;DF&gt;.transpose()                    <span class="hljs-comment"># Rotates the table.</span>
 &lt;DF&gt;    = &lt;DF&gt;.melt(id_vars=column_key/s)     <span class="hljs-comment"># Melts on columns.</span>
 </code></pre>
 <div><h4 id="operations-1">Operations:</h4><pre><code class="python language-python hljs">&lt;Sr&gt;    = &lt;DF&gt;.sum/max/mean/idxmax/all()
 &lt;DF&gt;    = &lt;DF&gt;.diff/cumsum/rank()             <span class="hljs-comment"># …/pct_change/fillna/ffill/interpolate()</span>
 <pre><code class="python language-python hljs">&lt;Sr&gt;    = &lt;DF&gt;.sum/max/mean/idxmax/all()
 &lt;Sr&gt;    = &lt;DF&gt;.apply/agg/transform(&lt;agg_func&gt;)
 &lt;DF&gt;    = &lt;DF&gt;.diff/cumsum/rank()             <span class="hljs-comment"># …/pct_change/fillna/ffill/interpolate()</span>
 &lt;DF&gt;    = &lt;DF&gt;.apply/agg/transform(&lt;trans_func&gt;)
 &lt;DF&gt;    = &lt;DF&gt;.applymap(&lt;func&gt;)               <span class="hljs-comment"># Apply a function to a Dataframe elementwise.</span>
 </code></pre></div>
 </code></pre>
 <ul>
 <li><strong>All operations operate on columns by default. Use <code class="python hljs"><span class="hljs-string">'axis=1'</span></code> parameter to process the rows instead.</strong> </li>
 </ul>
 <pre><code class="python language-python hljs">+-------------+------------+-----------+--------------+--------+-------------+---------------+
 |             |    <span class="hljs-string">'sum'</span>   |  [<span class="hljs-string">'sum'</span>]  | {<span class="hljs-string">'x'</span>: <span class="hljs-string">'sum'</span>} | <span class="hljs-string">'rank'</span> |  [<span class="hljs-string">'rank'</span>]   | {<span class="hljs-string">'x'</span>: <span class="hljs-string">'rank'</span>} |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | df.apply(…) |            |      x y  |              |    x y |      x    y |        x      |
 | df.agg(…)   |    x  <span class="hljs-number">4</span>    |  sum <span class="hljs-number">4</span> <span class="hljs-number">6</span>  |     x  <span class="hljs-number">4</span>     | a  <span class="hljs-number">1</span> <span class="hljs-number">1</span> |   rank rank |     a  <span class="hljs-number">1</span>      |
 | df.trans(…) |    y  <span class="hljs-number">6</span>    |           |              | b  <span class="hljs-number">2</span> <span class="hljs-number">2</span> | a    <span class="hljs-number">1</span>    <span class="hljs-number">1</span> |     b  <span class="hljs-number">2</span>      |
 |             |            |           |              |        | b    <span class="hljs-number">2</span>    <span class="hljs-number">2</span> |               |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 <div><h4 id="applyaggregatetransform">Apply, Aggregate, Transform:</h4><pre><code class="python language-python hljs"><span class="hljs-meta">&gt;&gt;&gt; </span>df = 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>])
   x  y
 a  <span class="hljs-number">1</span>  <span class="hljs-number">2</span>
 b  <span class="hljs-number">3</span>  <span class="hljs-number">4</span>
 </code></pre></div>
 <pre><code class="python language-python hljs">+-------------+---------------+---------------+---------------+
 |             |     <span class="hljs-string">'sum'</span>     |    [<span class="hljs-string">'sum'</span>]    | {<span class="hljs-string">'x'</span>: <span class="hljs-string">'sum'</span>}  |
 +-------------+---------------+---------------+---------------+
 | df.apply(…) |               |        x y    |               |
 | df.agg(…)   |     x  <span class="hljs-number">4</span>      |    sum <span class="hljs-number">4</span> <span class="hljs-number">6</span>    |     x  <span class="hljs-number">4</span>      |
 | df.trans(…) |     y  <span class="hljs-number">6</span>      |               |               |
 +-------------+---------------+---------------+---------------+
 </code></pre>
 <pre><code class="python language-python hljs">+-------------+---------------+---------------+---------------+
 |             |    <span class="hljs-string">'rank'</span>     |   [<span class="hljs-string">'rank'</span>]    | {<span class="hljs-string">'x'</span>: <span class="hljs-string">'rank'</span>} |
 +-------------+---------------+---------------+---------------+
 | df.apply(…) |       x  y    |       x    y  |        x      |
 | df.agg(…)   |    a  <span class="hljs-number">1</span>  <span class="hljs-number">1</span>    |    rank rank  |     a  <span class="hljs-number">1</span>      |
 | df.trans(…) |    b  <span class="hljs-number">2</span>  <span class="hljs-number">2</span>    |  a    <span class="hljs-number">1</span>    <span class="hljs-number">1</span>  |     b  <span class="hljs-number">2</span>      |
 |             |               |  b    <span class="hljs-number">2</span>    <span class="hljs-number">2</span>  |               |
 +-------------+---------------+---------------+---------------+
 </code></pre>
 <ul>
 <li><strong>Transform doesen't work with <code class="python hljs">[<span class="hljs-string">'sum'</span>]</code> and <code class="python hljs">{<span class="hljs-string">'x'</span>: <span class="hljs-string">'sum'</span>}</code>.</strong></li>
 <li><strong>Transform() doesen't work with <code class="python hljs">[<span class="hljs-string">'sum'</span>]</code> and <code class="python hljs">{<span class="hljs-string">'x'</span>: <span class="hljs-string">'sum'</span>}</code>.</strong></li>
 </ul>
 <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>])
   x  y 
@ -2757,36 +2781,53 @@ c  <span class="hljs-number">6</span>  <span class="hljs-number">7</span>
 <ul>
 <li><strong>Result of an operation is a dataframe with index made up of group keys. Use <code class="python hljs"><span class="hljs-string">'&lt;DF&gt;.reset_index()'</span></code> to move the index back into it's own column.</strong></li>
 </ul>
 <div><h4 id="operations-2">Operations:</h4><pre><code class="python language-python hljs">&lt;DF&gt; = &lt;GB&gt;.sum/max/mean/idxmax/all()
 &lt;DF&gt; = &lt;GB&gt;.diff/cumsum/rank()                <span class="hljs-comment"># …/pct_change/fillna/ffill()</span>
 <div><h4 id="aggregations-1">Aggregations:</h4><pre><code class="python language-python hljs">&lt;DF&gt; = &lt;GB&gt;.sum/max/mean/idxmax/all()
 &lt;DF&gt; = &lt;GB&gt;.apply/agg/transform(&lt;agg_func&gt;)
 </code></pre></div>
 <pre><code class="python language-python hljs">+-------------+------------+-------------+---------------+
 |             |    <span class="hljs-string">'sum'</span>   |   [<span class="hljs-string">'sum'</span>]   | {<span class="hljs-string">'x'</span>: <span class="hljs-string">'sum'</span>}  |
 +-------------+------------+-------------+---------------+
 | gb.apply(…) |    x  y  z |             |               |
 |             | z          |             |               |
 |             | <span class="hljs-number">3</span>  <span class="hljs-number">1</span>  <span class="hljs-number">2</span>  <span class="hljs-number">3</span> |             |               |
 |             | <span class="hljs-number">6</span> <span class="hljs-number">11</span> <span class="hljs-number">13</span> <span class="hljs-number">12</span> |             |               |
 +-------------+------------+-------------+---------------+
 | gb.agg(…)   |     x   y  |      x   y  |         x     |
 |             | z          |    sum sum  |     z         |
 |             | <span class="hljs-number">3</span>   <span class="hljs-number">1</span>   <span class="hljs-number">2</span>  |  z          |     <span class="hljs-number">3</span>   <span class="hljs-number">1</span>     |
 |             | <span class="hljs-number">6</span>  <span class="hljs-number">11</span>  <span class="hljs-number">13</span>  |  <span class="hljs-number">3</span>   <span class="hljs-number">1</span>   <span class="hljs-number">2</span>  |     <span class="hljs-number">6</span>  <span class="hljs-number">11</span>     |
 |             |            |  <span class="hljs-number">6</span>  <span class="hljs-number">11</span>  <span class="hljs-number">13</span>  |               |
 +-------------+------------+-------------+---------------+
 | gb.trans(…) |     x   y  |             |               |
 |             | a   <span class="hljs-number">1</span>   <span class="hljs-number">2</span>  |             |               |
 |             | b  <span class="hljs-number">11</span>  <span class="hljs-number">13</span>  |             |               |
 |             | c  <span class="hljs-number">11</span>  <span class="hljs-number">13</span>  |             |               |
 +-------------+------------+-------------+---------------+
 </code></pre>
 <div><h4 id="transformations-1">Transformations:</h4><pre><code class="python language-python hljs">&lt;DF&gt; = &lt;GB&gt;.diff/cumsum/rank()                <span class="hljs-comment"># …/pct_change/fillna/ffill()</span>
 &lt;DF&gt; = &lt;GB&gt;.agg/transform(&lt;trans_func&gt;)
 </code></pre></div>
 <pre><code class="python language-python hljs">+-------------+------------+-----------+--------------+--------+-------------+---------------+
 |             |    <span class="hljs-string">'sum'</span>   |  [<span class="hljs-string">'sum'</span>]  | {<span class="hljs-string">'x'</span>: <span class="hljs-string">'sum'</span>} | <span class="hljs-string">'rank'</span> |  [<span class="hljs-string">'rank'</span>]   | {<span class="hljs-string">'x'</span>: <span class="hljs-string">'rank'</span>} |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | gb.apply(…) |    x  y  z |           |              |        |             |               |
 |             | z          |           |              |        |             |               |
 |             | <span class="hljs-number">3</span>  <span class="hljs-number">1</span>  <span class="hljs-number">2</span>  <span class="hljs-number">3</span> |           |              |        |             |               |
 |             | <span class="hljs-number">6</span> <span class="hljs-number">11</span> <span class="hljs-number">13</span> <span class="hljs-number">12</span> |           |              |        |             |               |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | gb.agg(…)   |     x  y   |     x   y |        x     |    x y |      x    y |         x     |
 |             |  z         |   sum sum |     z        | a  <span class="hljs-number">1</span> <span class="hljs-number">1</span> |   rank rank |      a  <span class="hljs-number">1</span>     |
 |             |  <span class="hljs-number">3</span>  <span class="hljs-number">1</span>  <span class="hljs-number">2</span>   | z         |     <span class="hljs-number">3</span>  <span class="hljs-number">1</span>     | b  <span class="hljs-number">1</span> <span class="hljs-number">1</span> | a    <span class="hljs-number">1</span>    <span class="hljs-number">1</span> |      b  <span class="hljs-number">1</span>     |
 |             |  <span class="hljs-number">6</span> <span class="hljs-number">11</span> <span class="hljs-number">13</span>   | <span class="hljs-number">3</span>   <span class="hljs-number">1</span>   <span class="hljs-number">2</span> |     <span class="hljs-number">6</span> <span class="hljs-number">11</span>     | c  <span class="hljs-number">2</span> <span class="hljs-number">2</span> | b    <span class="hljs-number">1</span>    <span class="hljs-number">1</span> |      c  <span class="hljs-number">2</span>     |
 |             |            | <span class="hljs-number">6</span>  <span class="hljs-number">11</span>  <span class="hljs-number">13</span> |              |        | c    <span class="hljs-number">2</span>    <span class="hljs-number">2</span> |               |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 | gb.trans(…) |     x  y   |           |              |    x y |             |               |
 |             |  a  <span class="hljs-number">1</span>  <span class="hljs-number">2</span>   |           |              | a  <span class="hljs-number">1</span> <span class="hljs-number">1</span> |             |               |
 |             |  b <span class="hljs-number">11</span> <span class="hljs-number">13</span>   |           |              | b  <span class="hljs-number">1</span> <span class="hljs-number">1</span> |             |               |
 |             |  c <span class="hljs-number">11</span> <span class="hljs-number">13</span>   |           |              | c  <span class="hljs-number">1</span> <span class="hljs-number">1</span> |             |               |
 +-------------+------------+-----------+--------------+--------+-------------+---------------+
 <pre><code class="python language-python hljs">+-------------+------------+-------------+---------------+
 |             |   <span class="hljs-string">'rank'</span>   |  [<span class="hljs-string">'rank'</span>]   | {<span class="hljs-string">'x'</span>: <span class="hljs-string">'rank'</span>} |
 +-------------+------------+-------------+---------------+
 | gb.agg(…)   |     x  y   |      x    y |        x      |
 |             |  a  <span class="hljs-number">1</span>  <span class="hljs-number">1</span>   |   rank rank |     a  <span class="hljs-number">1</span>      |
 |             |  b  <span class="hljs-number">1</span>  <span class="hljs-number">1</span>   | a    <span class="hljs-number">1</span>    <span class="hljs-number">1</span> |     b  <span class="hljs-number">1</span>      |
 |             |  c  <span class="hljs-number">2</span>  <span class="hljs-number">2</span>   | b    <span class="hljs-number">1</span>    <span class="hljs-number">1</span> |     c  <span class="hljs-number">2</span>      |
 |             |            | c    <span class="hljs-number">2</span>    <span class="hljs-number">2</span> |               |
 +-------------+------------+-------------+---------------+
 | gb.trans(…) |     x  y   |             |               |
 |             |  a  <span class="hljs-number">1</span>  <span class="hljs-number">1</span>   |             |               |
 |             |  b  <span class="hljs-number">1</span>  <span class="hljs-number">1</span>   |             |               |
 |             |  c  <span class="hljs-number">1</span>  <span class="hljs-number">1</span>   |             |               |
 +-------------+------------+-------------+---------------+
 </code></pre>
 <div><h3 id="rolling">Rolling</h3><pre><code class="python language-python hljs">&lt;Rl_S/D/G&gt; = &lt;Sr/DF/GB&gt;.rolling(window_size)  <span class="hljs-comment"># Also: `min_periods=None, center=False`.</span>
 &lt;Rl_S/D&gt;   = &lt;Rl_D/G&gt;[column_key/s]           <span class="hljs-comment"># Or: &lt;Rl&gt;.column_key</span>
 &lt;Sr/DF/DF&gt; = &lt;Rl_S/D/G&gt;.sum/max/mean()
 &lt;Sr/DF/DF&gt; = &lt;Rl_S/D/G&gt;.apply(&lt;func&gt;)         <span class="hljs-comment"># Invokes function on every window.</span>
 &lt;Sr/DF/DF&gt; = &lt;Rl_S/D/G&gt;.apply(&lt;agg_func&gt;)     <span class="hljs-comment"># Invokes function on every window.</span>
 &lt;Sr/DF/DF&gt; = &lt;Rl_S/D/G&gt;.aggregate(&lt;func/str&gt;) <span class="hljs-comment"># Invokes function on every window.</span>
 </code></pre></div>