Pandas

README.md

@@ -3231,7 +3231,7 @@ plt.show()                                     # Displays the plot. Also plt.sav
 **Table with labeled rows and columns.**
 
 ```python
->>> l = pd.DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y']); l
+>>> df = pd.DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y']); df
    x  y
 a  1  2
 b  3  4
@@ -3251,7 +3251,7 @@ b  3  4
 
 ```python
 <S/DF> = <DF>[col_key/s]                       # Or: <DF>.<col_key>
-<DF>   = <DF>[row_bools]                       # Keeps rows as specified by bools.
+<DF>   = <DF>[<S_of_bools>]                    # Filters rows. For example `df[df.x > 1]`.
 <DF>   = <DF>[<DF_of_bools>]                   # Assigns NaN to items that are False in bools.
 ```
 
@@ -3270,7 +3270,7 @@ b  3  4
 ```python
 <DF>   = <DF>.head/tail/sample(<int>)          # Returns first, last, or random n rows.
 <DF>   = <DF>.describe()                       # Describes columns. Also info(), corr(), shape.
-<DF>   = <DF>.query('<query>')                 # Filters rows with e.g. 'col_1 == val_1 and …'.
+<DF>   = <DF>.query('<query>')                 # Filters rows. For example `df.query('x > 1')`.
 ```
 
 ```python
@@ -3280,37 +3280,37 @@ plt.show()                                     # Displays the plot. Also plt.sav
 
 #### DataFrame — Merge, Join, Concat:
 ```python
->>> r = pd.DataFrame([[4, 5], [6, 7]], index=['b', 'c'], columns=['y', 'z']); r
+>>> df_2 = pd.DataFrame([[4, 5], [6, 7]], index=['b', 'c'], columns=['y', 'z']); df_2
    y  z
 b  4  5
 c  6  7
 ```
 
 ```text
-+------------------------+---------------+------------+------------+--------------------------+
-|                        |    'outer'    |   'inner'  |   'left'   |       Description        |
-+------------------------+---------------+------------+------------+--------------------------+
-| l.merge(r, on='y',     |    x   y   z  | x   y   z  | x   y   z  | Merges on column if 'on' |
-|            how=…)      | 0  1   2   .  | 3   4   5  | 1   2   .  | or 'left/right_on' are   |
-|                        | 1  3   4   5  |            | 3   4   5  | set, else on shared cols.|
-|                        | 2  .   6   7  |            |            | Uses 'inner' by default. |
-+------------------------+---------------+------------+------------+--------------------------+
-| l.join(r, lsuffix='l', |    x yl yr  z |            | x yl yr  z | Merges on row keys.      |
-|           rsuffix='r', | a  1  2  .  . | x yl yr  z | 1  2  .  . | Uses 'left' by default.  |
-|           how=…)       | b  3  4  4  5 | 3  4  4  5 | 3  4  4  5 | If r is a Series, it is  |
-|                        | c  .  .  6  7 |            |            | treated as a column.     |
-+------------------------+---------------+------------+------------+--------------------------+
-| pd.concat([l, r],      |    x   y   z  |     y      |            | Adds rows at the bottom. |
-|           axis=0,      | a  1   2   .  |     2      |            | Uses 'outer' by default. |
-|           join=…)      | b  3   4   .  |     4      |            | A Series is treated as a |
-|                        | b  .   4   5  |     4      |            | column. To add a row use |
-|                        | c  .   6   7  |     6      |            | pd.concat([l, DF([s])]). |
-+------------------------+---------------+------------+------------+--------------------------+
-| pd.concat([l, r],      |    x  y  y  z |            |            | Adds columns at the      |
-|           axis=1,      | a  1  2  .  . | x  y  y  z |            | right end. Uses 'outer'  |
-|           join=…)      | b  3  4  4  5 | 3  4  4  5 |            | by default. A Series is  |
-|                        | c  .  .  6  7 |            |            | treated as a column.     |
-+------------------------+---------------+------------+------------+--------------------------+
++-----------------------+---------------+------------+------------+---------------------------+
+|                       |    'outer'    |   'inner'  |   'left'   |       Description         |
++-----------------------+---------------+------------+------------+---------------------------+
+| df.merge(df_2,        |    x   y   z  | x   y   z  | x   y   z  | Merges on column if 'on'  |
+|          on='y',      | 0  1   2   .  | 3   4   5  | 1   2   .  | or 'left/right_on' are    |
+|          how=…)       | 1  3   4   5  |            | 3   4   5  | set, else on shared cols. |
+|                       | 2  .   6   7  |            |            | Uses 'inner' by default.  |
++-----------------------+---------------+------------+------------+---------------------------+
+| df.join(df_2,         |    x yl yr  z |            | x yl yr  z | Merges on row keys.       |
+|         lsuffix='l',  | a  1  2  .  . | x yl yr  z | 1  2  .  . | Uses 'left' by default.   |
+|         rsuffix='r',  | b  3  4  4  5 | 3  4  4  5 | 3  4  4  5 | If r is a Series, it is   |
+|         how=…)        | c  .  .  6  7 |            |            | treated as a column.      |
++-----------------------+---------------+------------+------------+---------------------------+
+| pd.concat([df, df_2], |    x   y   z  |     y      |            | Adds rows at the bottom.  |
+|           axis=0,     | a  1   2   .  |     2      |            | Uses 'outer' by default.  |
+|           join=…)     | b  3   4   .  |     4      |            | A Series is treated as a  |
+|                       | b  .   4   5  |     4      |            | column. To add a row use  |
+|                       | c  .   6   7  |     6      |            | pd.concat([df, DF([s])]). |
++-----------------------+---------------+------------+------------+---------------------------+
+| pd.concat([df, df_2], |    x  y  y  z |            |            | Adds columns at the       |
+|           axis=1,     | a  1  2  .  . | x  y  y  z |            | right end. Uses 'outer'   |
+|           join=…)     | b  3  4  4  5 | 3  4  4  5 |            | by default. A Series is   |
+|                       | c  .  .  6  7 |            |            | treated as a column.      |
++-----------------------+---------------+------------+------------+---------------------------+
 ```
 
 #### DataFrame — Aggregate, Transform, Map:
@@ -3321,23 +3321,23 @@ c  6  7
 ```
 
 ```text
-+----------------+---------------+---------------+---------------+
-|                |     'sum'     |    ['sum']    | {'x': 'sum'}  |
-+----------------+---------------+---------------+---------------+
-| l.apply(…)     |      x  4     |        x  y   |     x  4      |
-| l.agg(…)       |      y  6     |   sum  4  6   |               |
-+----------------+---------------+---------------+---------------+
++-----------------+---------------+---------------+---------------+
+|                 |     'sum'     |    ['sum']    | {'x': 'sum'}  |
++-----------------+---------------+---------------+---------------+
+| df.apply(…)     |      x  4     |        x  y   |     x  4      |
+| df.agg(…)       |      y  6     |   sum  4  6   |               |
++-----------------+---------------+---------------+---------------+
 ```
 
 ```text
-+----------------+---------------+---------------+---------------+
-|                |     'rank'    |    ['rank']   | {'x': 'rank'} |
-+----------------+---------------+---------------+---------------+
-| l.apply(…)     |               |       x    y  |               |
-| l.agg(…)       |       x    y  |    rank rank  |         x     |
-| l.transform(…) |  a  1.0  1.0  |  a  1.0  1.0  |    a  1.0     |
-|                |  b  2.0  2.0  |  b  2.0  2.0  |    b  2.0     |
-+----------------+---------------+---------------+---------------+
++-----------------+---------------+---------------+---------------+
+|                 |     'rank'    |    ['rank']   | {'x': 'rank'} |
++-----------------+---------------+---------------+---------------+
+| df.apply(…)     |               |       x    y  |               |
+| df.agg(…)       |       x    y  |    rank rank  |         x     |
+| df.transform(…) |  a  1.0  1.0  |  a  1.0  1.0  |    a  1.0     |
+|                 |  b  2.0  2.0  |  b  2.0  2.0  |    b  2.0     |
++-----------------+---------------+---------------+---------------+
 ```
 * **All methods operate on columns by default. Pass `'axis=1'` to process the rows instead.**
 * **Fifth result's columns are indexed with a multi-index. This means we need a tuple of column keys to specify a column: `'<DF>.loc[row_key, (col_key_1, col_key_2)]'`.**

index.html

@@ -55,7 +55,7 @@
 
 <body>
   <header>
-    <aside>December 1, 2024</aside>
+    <aside>December 3, 2024</aside>
     <a href="https://gto76.github.io" rel="author">Jure Šorn</a>
   </header>
 
@@ -2631,7 +2631,7 @@ plt.show()                                     <span class="hljs-comment"># Disp
 <li><strong>Methods ffill(), interpolate(), fillna() and dropna() accept <code class="python hljs"><span class="hljs-string">'inplace=True'</span></code>.</strong></li>
 <li><strong>Last result has a multi-index. Use <code class="python hljs"><span class="hljs-string">'&lt;S&gt;[key_1, key_2]'</span></code> to get its values.</strong></li>
 </ul>
-<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>l = pd.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>]); l
+<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>df = pd.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>]); df
    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>
@@ -2647,7 +2647,7 @@ b  <span class="hljs-number">3</span>  <span class="hljs-number">4</span>
 &lt;DF&gt;   = &lt;DF&gt;.loc[row_bools, col_bools]        <span class="hljs-comment"># Or: &lt;DF&gt;.iloc[row_bools, col_bools]</span>
 </code></pre>
 <pre><code class="python language-python hljs">&lt;S/DF&gt; = &lt;DF&gt;[col_key/s]                       <span class="hljs-comment"># Or: &lt;DF&gt;.&lt;col_key&gt;</span>
-&lt;DF&gt;   = &lt;DF&gt;[row_bools]                       <span class="hljs-comment"># Keeps rows as specified by bools.</span>
+&lt;DF&gt;   = &lt;DF&gt;[&lt;S_of_bools&gt;]                    <span class="hljs-comment"># Filters rows. For example `df[df.x &gt; 1]`.</span>
 &lt;DF&gt;   = &lt;DF&gt;[&lt;DF_of_bools&gt;]                   <span class="hljs-comment"># Assigns NaN to items that are False in bools.</span>
 </code></pre>
 <pre><code class="python language-python hljs">&lt;DF&gt;   = &lt;DF&gt; &gt; &lt;el/S/DF&gt;                      <span class="hljs-comment"># Returns DF of bools. S is treated as a row.</span>
@@ -2660,62 +2660,62 @@ b  <span class="hljs-number">3</span>  <span class="hljs-number">4</span>
 </code></pre>
 <pre><code class="python language-python hljs">&lt;DF&gt;   = &lt;DF&gt;.head/tail/sample(&lt;int&gt;)          <span class="hljs-comment"># Returns first, last, or random n rows.</span>
 &lt;DF&gt;   = &lt;DF&gt;.describe()                       <span class="hljs-comment"># Describes columns. Also info(), corr(), shape.</span>
-&lt;DF&gt;   = &lt;DF&gt;.query(<span class="hljs-string">'&lt;query&gt;'</span>)                 <span class="hljs-comment"># Filters rows with e.g. 'col_1 == val_1 and …'.</span>
+&lt;DF&gt;   = &lt;DF&gt;.query(<span class="hljs-string">'&lt;query&gt;'</span>)                 <span class="hljs-comment"># Filters rows. For example `df.query('x &gt; 1')`.</span>
 </code></pre>
 <pre><code class="python language-python hljs">&lt;DF&gt;.plot.line/area/bar/scatter(x=col_key, …)  <span class="hljs-comment"># `y=col_key/s`. Also hist/box(by=col_key).</span>
 plt.show()                                     <span class="hljs-comment"># Displays the plot. Also plt.savefig(&lt;path&gt;).</span>
 </code></pre>
-<div><h4 id="dataframemergejoinconcat">DataFrame — Merge, Join, Concat:</h4><pre><code class="python language-python hljs"><span class="hljs-meta">&gt;&gt;&gt; </span>r = pd.DataFrame([[<span class="hljs-number">4</span>, <span class="hljs-number">5</span>], [<span class="hljs-number">6</span>, <span class="hljs-number">7</span>]], index=[<span class="hljs-string">'b'</span>, <span class="hljs-string">'c'</span>], columns=[<span class="hljs-string">'y'</span>, <span class="hljs-string">'z'</span>]); r
+<div><h4 id="dataframemergejoinconcat">DataFrame — Merge, Join, Concat:</h4><pre><code class="python language-python hljs"><span class="hljs-meta">&gt;&gt;&gt; </span>df_2 = pd.DataFrame([[<span class="hljs-number">4</span>, <span class="hljs-number">5</span>], [<span class="hljs-number">6</span>, <span class="hljs-number">7</span>]], index=[<span class="hljs-string">'b'</span>, <span class="hljs-string">'c'</span>], columns=[<span class="hljs-string">'y'</span>, <span class="hljs-string">'z'</span>]); df_2
    y  z
 b  <span class="hljs-number">4</span>  <span class="hljs-number">5</span>
 c  <span class="hljs-number">6</span>  <span class="hljs-number">7</span>
 </code></pre></div>
 
-<pre><code class="python hljs">┏━━━━━━━━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━┓
-┃                        │    <span class="hljs-string">'outer'</span>    │   <span class="hljs-string">'inner'</span>  │   <span class="hljs-string">'left'</span>   │       Description        ┃
-┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨
-┃ l.merge(r, on=<span class="hljs-string">'y'</span>,     │    x   y   z  │ x   y   z  │ x   y   z  │ Merges on column if <span class="hljs-string">'on'</span> ┃
-┃            how=…)      │ <span class="hljs-number">0</span>  <span class="hljs-number">1</span>   <span class="hljs-number">2</span>   .  │ <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │ <span class="hljs-number">1</span>   <span class="hljs-number">2</span>   .  │ or <span class="hljs-string">'left/right_on'</span> are   ┃
-┃                        │ <span class="hljs-number">1</span>  <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │            │ <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │ set, else on shared cols.┃
-┃                        │ <span class="hljs-number">2</span>  .   <span class="hljs-number">6</span>   <span class="hljs-number">7</span>  │            │            │ Uses <span class="hljs-string">'inner'</span> by default. ┃
-┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨
-┃ l.join(r, lsuffix=<span class="hljs-string">'l'</span>, │    x yl yr  z │            │ x yl yr  z │ Merges on row keys.      ┃
-┃           rsuffix=<span class="hljs-string">'r'</span>, │ a  <span class="hljs-number">1</span>  <span class="hljs-number">2</span>  .  . │ x yl yr  z │ <span class="hljs-number">1</span>  <span class="hljs-number">2</span>  .  . │ Uses <span class="hljs-string">'left'</span> by default.  ┃
-┃           how=…)       │ b  <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │ <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │ <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │ If r is a Series, it is  ┃
-┃                        │ c  .  .  <span class="hljs-number">6</span>  <span class="hljs-number">7</span> │            │            │ treated as a column.     ┃
-┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨
-┃ pd.concat([l, r],      │    x   y   z  │     y      │            │ Adds rows at the bottom. ┃
-┃           axis=<span class="hljs-number">0</span>,      │ a  <span class="hljs-number">1</span>   <span class="hljs-number">2</span>   .  │     <span class="hljs-number">2</span>      │            │ Uses <span class="hljs-string">'outer'</span> by default. ┃
-┃           join=…)      │ b  <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   .  │     <span class="hljs-number">4</span>      │            │ A Series is treated as a ┃
-┃                        │ b  .   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │     <span class="hljs-number">4</span>      │            │ column. To add a row use ┃
-┃                        │ c  .   <span class="hljs-number">6</span>   <span class="hljs-number">7</span>  │     <span class="hljs-number">6</span>      │            │ pd.concat([l, DF([s])]). ┃
-┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨
-┃ pd.concat([l, r],      │    x  y  y  z │            │            │ Adds columns at the      ┃
-┃           axis=<span class="hljs-number">1</span>,      │ a  <span class="hljs-number">1</span>  <span class="hljs-number">2</span>  .  . │ x  y  y  z │            │ right end. Uses <span class="hljs-string">'outer'</span>  ┃
-┃           join=…)      │ b  <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │ <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │            │ by default. A Series is  ┃
-┃                        │ c  .  .  <span class="hljs-number">6</span>  <span class="hljs-number">7</span> │            │            │ treated as a column.     ┃
-┗━━━━━━━━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━┛
+<pre><code class="python hljs">┏━━━━━━━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
+┃                       │    <span class="hljs-string">'outer'</span>    │   <span class="hljs-string">'inner'</span>  │   <span class="hljs-string">'left'</span>   │       Description         ┃
+┠───────────────────────┼───────────────┼────────────┼────────────┼───────────────────────────┨
+┃ df.merge(df_2,        │    x   y   z  │ x   y   z  │ x   y   z  │ Merges on column if 'on'  ┃
+┃          on=<span class="hljs-string">'y'</span>,      │ <span class="hljs-number">0</span>  <span class="hljs-number">1</span>   <span class="hljs-number">2</span>   .  │ <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │ <span class="hljs-number">1</span>   <span class="hljs-number">2</span>   .  │ or 'left/right_on' are    ┃
+┃          how=…)       │ <span class="hljs-number">1</span>  <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │            │ <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │ set, else on shared cols. ┃
+┃                       │ <span class="hljs-number">2</span>  .   <span class="hljs-number">6</span>   <span class="hljs-number">7</span>  │            │            │ Uses <span class="hljs-string">'inner'</span> by default.  ┃
+┠───────────────────────┼───────────────┼────────────┼────────────┼───────────────────────────┨
+┃ df.join(df_2,         │    x yl yr  z │            │ x yl yr  z │ Merges on row keys.       ┃
+┃         lsuffix=<span class="hljs-string">'l'</span>,  │ a  <span class="hljs-number">1</span>  <span class="hljs-number">2</span>  .  . │ x yl yr  z │ <span class="hljs-number">1</span>  <span class="hljs-number">2</span>  .  . │ Uses <span class="hljs-string">'left'</span> by default.   ┃
+┃         rsuffix=<span class="hljs-string">'r'</span>,  │ b  <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │ <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │ <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │ If r is a Series, it is   ┃
+┃         how=…)        │ c  .  .  <span class="hljs-number">6</span>  <span class="hljs-number">7</span> │            │            │ treated as a column.      ┃
+┠───────────────────────┼───────────────┼────────────┼────────────┼───────────────────────────┨
+┃ pd.concat([df, df_2], │    x   y   z  │     y      │            │ Adds rows at the bottom.  ┃
+┃           axis=<span class="hljs-number">0</span>,     │ a  <span class="hljs-number">1</span>   <span class="hljs-number">2</span>   .  │     <span class="hljs-number">2</span>      │            │ Uses <span class="hljs-string">'outer'</span> by default.  ┃
+┃           join=…)     │ b  <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   .  │     <span class="hljs-number">4</span>      │            │ A Series is treated as a  ┃
+┃                       │ b  .   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │     <span class="hljs-number">4</span>      │            │ column. To add a row use  ┃
+┃                       │ c  .   <span class="hljs-number">6</span>   <span class="hljs-number">7</span>  │     <span class="hljs-number">6</span>      │            │ pd.concat([df, DF([s])]). ┃
+┠───────────────────────┼───────────────┼────────────┼────────────┼───────────────────────────┨
+┃ pd.concat([df, df_2], │    x  y  y  z │            │            │ Adds columns at the       ┃
+┃           axis=<span class="hljs-number">1</span>,     │ a  <span class="hljs-number">1</span>  <span class="hljs-number">2</span>  .  . │ x  y  y  z │            │ right end. Uses <span class="hljs-string">'outer'</span>   ┃
+┃           join=…)     │ b  <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │ <span class="hljs-number">3</span>  <span class="hljs-number">4</span>  <span class="hljs-number">4</span>  <span class="hljs-number">5</span> │            │ by default. A Series is   ┃
+┃                       │ c  .  .  <span class="hljs-number">6</span>  <span class="hljs-number">7</span> │            │            │ treated as a column.      ┃
+┗━━━━━━━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
 </code></pre>
 <div><h4 id="dataframeaggregatetransformmap">DataFrame — Aggregate, Transform, Map:</h4><pre><code class="python language-python hljs">&lt;S&gt;  = &lt;DF&gt;.sum/max/mean/idxmax/all()          <span class="hljs-comment"># Or: &lt;DF&gt;.apply/agg(lambda &lt;S&gt;: &lt;el&gt;)</span>
 &lt;DF&gt; = &lt;DF&gt;.rank/diff/cumsum/ffill/interpo…()  <span class="hljs-comment"># Or: &lt;DF&gt;.apply/agg/transform(lambda &lt;S&gt;: &lt;S&gt;)</span>
 &lt;DF&gt; = &lt;DF&gt;.isna/fillna/isin([&lt;el/coll&gt;])      <span class="hljs-comment"># Or: &lt;DF&gt;.applymap(lambda &lt;el&gt;: &lt;el&gt;)</span>
 </code></pre></div>
 
-<pre><code class="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>}  ┃
-┠────────────────┼───────────────┼───────────────┼───────────────┨
-┃ l.apply(…)     │      x  <span class="hljs-number">4</span>     │        x  y   │     x  <span class="hljs-number">4</span>      ┃
-┃ l.agg(…)       │      y  <span class="hljs-number">6</span>     │   sum  <span class="hljs-number">4</span>  <span class="hljs-number">6</span>   │               ┃
-┗━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛
+<pre><code class="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  <span class="hljs-number">4</span>     │        x  y   │     x  <span class="hljs-number">4</span>      ┃
+┃ df.agg(…)       │      y  <span class="hljs-number">6</span>     │   sum  <span class="hljs-number">4</span>  <span class="hljs-number">6</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>} ┃
-┠────────────────┼───────────────┼───────────────┼───────────────┨
-┃ l.apply(…)     │               │       x    y  │               ┃
-┃ l.agg(…)       │       x    y  │    rank rank  │         x     ┃
-┃ l.transform(…) │  a  <span class="hljs-number">1.0</span>  <span class="hljs-number">1.0</span>  │  a  <span class="hljs-number">1.0</span>  <span class="hljs-number">1.0</span>  │    a  <span class="hljs-number">1.0</span>     ┃
-┃                │  b  <span class="hljs-number">2.0</span>  <span class="hljs-number">2.0</span>  │  b  <span class="hljs-number">2.0</span>  <span class="hljs-number">2.0</span>  │    b  <span class="hljs-number">2.0</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  │               ┃
+┃ df.agg(…)       │       x    y  │    rank rank  │         x     ┃
+┃ df.transform(…) │  a  <span class="hljs-number">1.0</span>  <span class="hljs-number">1.0</span>  │  a  <span class="hljs-number">1.0</span>  <span class="hljs-number">1.0</span>  │    a  <span class="hljs-number">1.0</span>     ┃
+┃                 │  b  <span class="hljs-number">2.0</span>  <span class="hljs-number">2.0</span>  │  b  <span class="hljs-number">2.0</span>  <span class="hljs-number">2.0</span>  │    b  <span class="hljs-number">2.0</span>     ┃
+┗━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛
 </code></pre>
 
 <ul>
@@ -2924,7 +2924,7 @@ $ deactivate                <span class="hljs-comment"># Deactivates the active
  
 
   <footer>
-    <aside>December 1, 2024</aside>
+    <aside>December 3, 2024</aside>
     <a href="https://gto76.github.io" rel="author">Jure Šorn</a>
   </footer>
 

parse.js

@@ -599,56 +599,57 @@ const DIAGRAM_14_A =
   "|              |    'rank'   |   ['rank']  | {'r': 'rank'} |";
 
 const DIAGRAM_15_A =
-  '+------------------------+---------------+------------+------------+--------------------------+';
+  '+-----------------------+---------------+------------+------------+---------------------------+';
 
 const DIAGRAM_15_B =
-  "┏━━━━━━━━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n" +
-  "┃                        │    'outer'    │   'inner'  │   'left'   │       Description        ┃\n" +
-  "┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨\n" +
-  "┃ l.merge(r, on='y',     │    x   y   z  │ x   y   z  │ x   y   z  │ Merges on column if 'on' ┃\n" +
-  "┃            how=…)      │ 0  1   2   .  │ 3   4   5  │ 1   2   .  │ or 'left/right_on' are   ┃\n" +
-  "┃                        │ 1  3   4   5  │            │ 3   4   5  │ set, else on shared cols.┃\n" +
-  "┃                        │ 2  .   6   7  │            │            │ Uses 'inner' by default. ┃\n" +
-  "┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨\n" +
-  "┃ l.join(r, lsuffix='l', │    x yl yr  z │            │ x yl yr  z │ Merges on row keys.      ┃\n" +
-  "┃           rsuffix='r', │ a  1  2  .  . │ x yl yr  z │ 1  2  .  . │ Uses 'left' by default.  ┃\n" +
-  "┃           how=…)       │ b  3  4  4  5 │ 3  4  4  5 │ 3  4  4  5 │ If r is a Series, it is  ┃\n" +
-  "┃                        │ c  .  .  6  7 │            │            │ treated as a column.     ┃\n" +
-  "┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨\n" +
-  "┃ pd.concat([l, r],      │    x   y   z  │     y      │            │ Adds rows at the bottom. ┃\n" +
-  "┃           axis=0,      │ a  1   2   .  │     2      │            │ Uses 'outer' by default. ┃\n" +
-  "┃           join=…)      │ b  3   4   .  │     4      │            │ A Series is treated as a ┃\n" +
-  "┃                        │ b  .   4   5  │     4      │            │ column. To add a row use ┃\n" +
-  "┃                        │ c  .   6   7  │     6      │            │ pd.concat([l, DF([s])]). ┃\n" +
-  "┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨\n" +
-  "┃ pd.concat([l, r],      │    x  y  y  z │            │            │ Adds columns at the      ┃\n" +
-  "┃           axis=1,      │ a  1  2  .  . │ x  y  y  z │            │ right end. Uses 'outer'  ┃\n" +
-  "┃           join=…)      │ b  3  4  4  5 │ 3  4  4  5 │            │ by default. A Series is  ┃\n" +
-  "┃                        │ c  .  .  6  7 │            │            │ treated as a column.     ┃\n" +
-  "┗━━━━━━━━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━┛\n";
+  "┏━━━━━━━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n" +
+  "┃                       │    'outer'    │   'inner'  │   'left'   │       Description         ┃\n" +
+  "┠───────────────────────┼───────────────┼────────────┼────────────┼───────────────────────────┨\n" +
+  "┃ df.merge(df_2,        │    x   y   z  │ x   y   z  │ x   y   z  │ Merges on column if 'on'  ┃\n" +
+  "┃          on='y',      │ 0  1   2   .  │ 3   4   5  │ 1   2   .  │ or 'left/right_on' are    ┃\n" +
+  "┃          how=…)       │ 1  3   4   5  │            │ 3   4   5  │ set, else on shared cols. ┃\n" +
+  "┃                       │ 2  .   6   7  │            │            │ Uses 'inner' by default.  ┃\n" +
+  "┠───────────────────────┼───────────────┼────────────┼────────────┼───────────────────────────┨\n" +
+  "┃ df.join(df_2,         │    x yl yr  z │            │ x yl yr  z │ Merges on row keys.       ┃\n" +
+  "┃         lsuffix='l',  │ a  1  2  .  . │ x yl yr  z │ 1  2  .  . │ Uses 'left' by default.   ┃\n" +
+  "┃         rsuffix='r',  │ b  3  4  4  5 │ 3  4  4  5 │ 3  4  4  5 │ If r is a Series, it is   ┃\n" +
+  "┃         how=…)        │ c  .  .  6  7 │            │            │ treated as a column.      ┃\n" +
+  "┠───────────────────────┼───────────────┼────────────┼────────────┼───────────────────────────┨\n" +
+  "┃ pd.concat([df, df_2], │    x   y   z  │     y      │            │ Adds rows at the bottom.  ┃\n" +
+  "┃           axis=0,     │ a  1   2   .  │     2      │            │ Uses 'outer' by default.  ┃\n" +
+  "┃           join=…)     │ b  3   4   .  │     4      │            │ A Series is treated as a  ┃\n" +
+  "┃                       │ b  .   4   5  │     4      │            │ column. To add a row use  ┃\n" +
+  "┃                       │ c  .   6   7  │     6      │            │ pd.concat([df, DF([s])]). ┃\n" +
+  "┠───────────────────────┼───────────────┼────────────┼────────────┼───────────────────────────┨\n" +
+  "┃ pd.concat([df, df_2], │    x  y  y  z │            │            │ Adds columns at the       ┃\n" +
+  "┃           axis=1,     │ a  1  2  .  . │ x  y  y  z │            │ right end. Uses 'outer'   ┃\n" +
+  "┃           join=…)     │ b  3  4  4  5 │ 3  4  4  5 │            │ by default. A Series is   ┃\n" +
+  "┃                       │ c  .  .  6  7 │            │            │ treated as a column.      ┃\n" +
+  "┗━━━━━━━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━━┛\n";
+
 
 const DIAGRAM_16_A =
-  '| l.apply(…)     |      x  4     |        x  y   |     x  4      |';
+  '| df.apply(…)     |      x  4     |        x  y   |     x  4      |';
 
 const DIAGRAM_16_B =
-  "┏━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓\n" +
-  "┃                │     'sum'     │    ['sum']    │ {'x': 'sum'}  ┃\n" +
-  "┠────────────────┼───────────────┼───────────────┼───────────────┨\n" +
-  "┃ l.apply(…)     │      x  4     │        x  y   │     x  4      ┃\n" +
-  "┃ l.agg(…)       │      y  6     │   sum  4  6   │               ┃\n" +
-  "┗━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛\n" +
+  "┏━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓\n" +
+  "┃                 │     'sum'     │    ['sum']    │ {'x': 'sum'}  ┃\n" +
+  "┠─────────────────┼───────────────┼───────────────┼───────────────┨\n" +
+  "┃ df.apply(…)     │      x  4     │        x  y   │     x  4      ┃\n" +
+  "┃ df.agg(…)       │      y  6     │   sum  4  6   │               ┃\n" +
+  "┗━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛\n" +
   "\n" +
-  "┏━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓\n" +
-  "┃                │     'rank'    │    ['rank']   │ {'x': 'rank'} ┃\n" +
-  "┠────────────────┼───────────────┼───────────────┼───────────────┨\n" +
-  "┃ l.apply(…)     │               │       x    y  │               ┃\n" +
-  "┃ l.agg(…)       │       x    y  │    rank rank  │         x     ┃\n" +
-  "┃ l.transform(…) │  a  1.0  1.0  │  a  1.0  1.0  │    a  1.0     ┃\n" +
-  "┃                │  b  2.0  2.0  │  b  2.0  2.0  │    b  2.0     ┃\n" +
-  "┗━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛\n";
+  "┏━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓\n" +
+  "┃                 │     'rank'    │    ['rank']   │ {'x': 'rank'} ┃\n" +
+  "┠─────────────────┼───────────────┼───────────────┼───────────────┨\n" +
+  "┃ df.apply(…)     │               │       x    y  │               ┃\n" +
+  "┃ df.agg(…)       │       x    y  │    rank rank  │         x     ┃\n" +
+  "┃ df.transform(…) │  a  1.0  1.0  │  a  1.0  1.0  │    a  1.0     ┃\n" +
+  "┃                 │  b  2.0  2.0  │  b  2.0  2.0  │    b  2.0     ┃\n" +
+  "┗━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛\n";
 
 const DIAGRAM_17_A =
-  "|                |     'rank'    |    ['rank']   | {'x': 'rank'} |";
+  "|                 |     'rank'    |    ['rank']   | {'x': 'rank'} |";
 
 const DIAGRAM_18_A =
   '| gb.agg(…)       |      x   y  |             |      x    y |               |';
@@ -897,7 +898,7 @@ function insertPageBreakBefore(an_id) {
 }
 
 function fixPandasDiagram() {
-  const diagram_15 = '┏━━━━━━━━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━┓';
+  const diagram_15 = '┏━━━━━━━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━━┓';
   $(`code:contains(${diagram_15})`).find(".hljs-keyword:contains(and)").after("and");
   $(`code:contains(${diagram_15})`).find(".hljs-keyword:contains(as)").after("as");
   $(`code:contains(${diagram_15})`).find(".hljs-keyword:contains(is)").after("is");
@@ -905,6 +906,10 @@ function fixPandasDiagram() {
   $(`code:contains(${diagram_15})`).find(".hljs-keyword:contains(or)").after("or");
   $(`code:contains(${diagram_15})`).find(".hljs-keyword:contains(else)").after("else");
   $(`code:contains(${diagram_15})`).find(".hljs-keyword").remove();
+  $(`code:contains(${diagram_15})`).find(".hljs-string:contains(\'left/right_on\')").after("\'left/right_on\'");
+  $(`code:contains(${diagram_15})`).find(".hljs-string:contains(\'left/right_on\')").remove();
+  $(`code:contains(${diagram_15})`).find(".hljs-string:contains('on')").after("'on'");
+  $(`code:contains(${diagram_15})`).find(".hljs-string:contains('on')").remove();
 }
 
 function removePlotImages() {