Pandas

README.md

@@ -3180,9 +3180,9 @@ b  3  4
 
 ```python
 <DF>    = <DF>.set_index(column_key)          # Replaces row keys with values from a column.
-<DF>    = <DF>.reset_index()                  # Moves row keys to column named index.
+<DF>    = <DF>.reset_index()                  # Moves row keys to a column named index.
 <DF>    = <DF>.filter('<regex>', axis=1)      # Only keeps columns whose key matches the regex.
-<DF>    = <DF>.melt(id_vars=column_key/s)     # Converts DF from wide to long format.
+<DF>    = <DF>.melt(id_vars=column_key/s)     # Converts DataFrame from wide to long format.
 ```
 
 #### Merge, Join, Concat:
@@ -3224,7 +3224,7 @@ c  6  7
 +------------------------+---------------+------------+------------+--------------------------+
 | l.combine_first(r)     |    x   y   z  |            |            | Adds missing rows and    |
 |                        | a  1   2   .  |            |            | columns. Also updates    |
-|                        | b  3   4   5  |            |            | cells that contain NaN.  |
+|                        | b  3   4   5  |            |            | items that contain NaN.  |
 |                        | c  .   6   7  |            |            | R must be a DataFrame.   |
 +------------------------+---------------+------------+------------+--------------------------+
 ```

index.html

@@ -2721,9 +2721,9 @@ b  <span class="hljs-number">3</span>  <span class="hljs-number">4</span>
 &lt;DF&gt;    = &lt;DF&gt; +-*/ &lt;el/Sr/DF&gt;                <span class="hljs-comment"># Items with non-matching keys get value NaN.</span>
 </code></pre>
 <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>
-&lt;DF&gt;    = &lt;DF&gt;.reset_index()                  <span class="hljs-comment"># Moves row keys to column named index.</span>
+&lt;DF&gt;    = &lt;DF&gt;.reset_index()                  <span class="hljs-comment"># Moves row keys to a column named index.</span>
 &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>
-&lt;DF&gt;    = &lt;DF&gt;.melt(id_vars=column_key/s)     <span class="hljs-comment"># Converts DF from wide to long format.</span>
+&lt;DF&gt;    = &lt;DF&gt;.melt(id_vars=column_key/s)     <span class="hljs-comment"># Converts DataFrame from wide to long format.</span>
 </code></pre>
 <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 
@@ -2761,7 +2761,7 @@ c  <span class="hljs-number">6</span>  <span class="hljs-number">7</span>
 ┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨
 ┃ l.combine_first(r)     │    x   y   z  │            │            │ Adds missing rows and    ┃
 ┃                        │ a  <span class="hljs-number">1</span>   <span class="hljs-number">2</span>   .  │            │            │ columns. Also updates    ┃
-┃                        │ b  <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │            │            │ cells that contain NaN.  ┃
+┃                        │ b  <span class="hljs-number">3</span>   <span class="hljs-number">4</span>   <span class="hljs-number">5</span>  │            │            │ items that contain NaN.  ┃
 ┃                        │ c  .   <span class="hljs-number">6</span>   <span class="hljs-number">7</span>  │            │            │ R must be a DataFrame.   ┃
 ┗━━━━━━━━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━┛
 </code></pre>

parse.js

@@ -362,7 +362,7 @@ const DIAGRAM_15_B =
   "┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨\n" +
   "┃ l.combine_first(r)     │    x   y   z  │            │            │ Adds missing rows and    ┃\n" +
   "┃                        │ a  1   2   .  │            │            │ columns. Also updates    ┃\n" +
-  "┃                        │ b  3   4   5  │            │            │ cells that contain NaN.  ┃\n" +
+  "┃                        │ b  3   4   5  │            │            │ items that contain NaN.  ┃\n" +
   "┃                        │ c  .   6   7  │            │            │ R must be a DataFrame.   ┃\n" +
   "┗━━━━━━━━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━┛\n";