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 * **`'$ pip3 install "pandas[excel]" odfpy lxml pyarrow'` installs dependencies.**
 * **Read\_csv() only parses dates of columns that were specified by 'parse\_dates' argument. It automatically tries to detect the format, but it can be helped with 'date\_format' or 'dayfirst' arguments. Both dates and datetimes get stored as pd.Timestamp objects.**
 * **If there's a single invalid date then it returns the whole column as a series of strings, unlike `'<S> = pd.to_datetime(<S>, errors="coerce")'`, which uses pd.NaT.**
-* **To get specific attributes from a series of Timestamps use `'<S>.dt.year/date/…'`.**
 
 ### GroupBy
 **Object that groups together rows of a dataframe based on the value of the passed column.**
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 <li><strong><code class="python hljs"><span class="hljs-string">'$ pip3 install "pandas[excel]" odfpy lxml pyarrow'</span></code> installs dependencies.</strong></li>
 <li><strong>Read_csv() only parses dates of columns that were specified by 'parse_dates' argument. It&nbsp;automatically tries to detect the format, but it can be helped with 'date_format' or 'dayfirst' arguments. Both dates and datetimes get stored as pd.Timestamp objects.</strong></li>
 <li><strong>If there's a single invalid date then it returns the whole column as a series of strings, unlike <code class="python hljs"><span class="hljs-string">'&lt;S&gt; = pd.to_datetime(&lt;S&gt;, errors="coerce")'</span></code>, which uses pd.NaT.</strong></li>
-<li><strong>To get specific attributes from a series of Timestamps use <code class="python hljs"><span class="hljs-string">'&lt;S&gt;.dt.year/date/…'</span></code>.</strong></li>
 </ul>
 <div><h3 id="groupby">GroupBy</h3><p><strong>Object that groups together rows of a dataframe based on the value of the passed column.</strong></p><pre><code class="python language-python hljs">&lt;GB&gt; = &lt;DF&gt;.groupby(col_key/s)                 <span class="hljs-comment"># Splits DF into groups based on passed column.</span>
 &lt;DF&gt; = &lt;GB&gt;.apply/filter(&lt;func&gt;)               <span class="hljs-comment"># Filter drops a group if func returns False.</span>