Pandas

Author: gto76

README.md

@@ -3103,7 +3103,7 @@ Name: a, dtype: int64
 
 ```python
 <Sr> = <Sr> ><== <el/Sr> # Returns a Series of bools.
-<Sr> = <Sr> +-*/ <el/Sr> # Non-matching keys get value NaN.
+<Sr> = <Sr> +-*/ <el/Sr> # Items with non-matching keys get value NaN.
 ```
 
 ```python
@@ -3176,7 +3176,7 @@ b 3 4
 
 ```python
 <DF> = <DF> ><== <el/Sr/DF> # Returns DataFrame of bools.
-<DF> = <DF> +-*/ <el/Sr/DF> # Non-matching keys get value NaN.
+<DF> = <DF> +-*/ <el/Sr/DF> # Items with non-matching keys get value NaN.
 ```
 
 ```python
@@ -3298,7 +3298,7 @@ c 7 8
 
 ```python
 <GB> = <DF>.groupby(column_key/s) # DF is split into groups based on passed column.
-<DF> = <GB>.get_group(group_key)  # Selects a group by value of grouping column.
+<DF> = <GB>.get_group(group_key/s) # Selects a group by value of grouping column.
 ```
 
 #### Aggregate, Transform, Map:

index.html

@@ -2650,7 +2650,7 @@
 &lt;Sr&gt; = &lt;Sr&gt;[bools] <span class="hljs-comment"># Or: &lt;Sr&gt;.i/loc[bools]</span>
 </code></pre>
 <pre><code class="python language-python hljs">&lt;Sr&gt; = &lt;Sr&gt; &gt;&lt;== &lt;el/Sr&gt; <span class="hljs-comment"># Returns a Series of bools.</span>
-&lt;Sr&gt; = &lt;Sr&gt; +-*/ &lt;el/Sr&gt; <span class="hljs-comment"># Non-matching keys get value NaN.</span>
+&lt;Sr&gt; = &lt;Sr&gt; +-*/ &lt;el/Sr&gt; <span class="hljs-comment"># Items with non-matching keys get value NaN.</span>
 </code></pre>
 <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.</span>
@@ -2706,7 +2706,7 @@
 &lt;DF&gt; = &lt;DF&gt;[&lt;DF_of_bools&gt;] <span class="hljs-comment"># Assigns NaN to False values.</span>
 </code></pre>
 <pre><code class="python language-python hljs">&lt;DF&gt; = &lt;DF&gt; &gt;&lt;== &lt;el/Sr/DF&gt; <span class="hljs-comment"># Returns DataFrame of bools.</span>
-&lt;DF&gt; = &lt;DF&gt; +-*/ &lt;el/Sr/DF&gt; <span class="hljs-comment"># Non-matching keys get value NaN.</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 their own column.</span>
@@ -2809,7 +2809,7 @@
 
 
 <pre><code class="python language-python hljs">&lt;GB&gt; = &lt;DF&gt;.groupby(column_key/s) <span class="hljs-comment"># DF is split into groups based on passed column.</span>
-&lt;DF&gt; = &lt;GB&gt;.get_group(group_key)  <span class="hljs-comment"># Selects a group by value of grouping column.</span>
+&lt;DF&gt; = &lt;GB&gt;.get_group(group_key/s) <span class="hljs-comment"># Selects a group by value of grouping column.</span>
 </code></pre>
 <div><h4 id="aggregatetransformmap-2">Aggregate, Transform, Map:</h4><pre><code class="python language-python hljs">&lt;DF&gt; = &lt;GB&gt;.sum/max/mean/idxmax/all() <span class="hljs-comment"># Or: &lt;GB&gt;.apply/agg(&lt;agg_func&gt;)</span>
 &lt;DF&gt; = &lt;GB&gt;.rank/diff/cumsum/ffill() <span class="hljs-comment"># Or: &lt;GB&gt;.aggregate(&lt;trans_func&gt;) </span>