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Pandas csv bullets

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Jure Šorn 1 month ago
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  1. 5
      README.md
  2. 9
      index.html

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README.md
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@ -3365,8 +3365,9 @@ c 6 7
<DF>.to_sql('<table_name>', <connection>) # Also `if_exists='fail/replace/append'`.
```
* **`'$ 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 'parse\_dates' and 'index_col' are the same column, we get a DF with DatetimeIndex. Its `'resample("y/m/d/h")'` method returns a Resampler object that is similar to GroupBy.**
* **Csv functions use the same dialect as standard library's csv module (e.g. `'sep=","'`).**
* **Read\_csv() only parses dates of columns that are listed in 'parse\_dates'. It automatically tries to detect the format, but it can be helped with 'date\_format' or 'dayfirst' arguments.**
* **We get a dataframe with DatetimeIndex if 'parse_dates' argument includes 'index\_col'. Its `'resample("y/m/d/h")'` method returns Resampler object that is similar to GroupBy.**
### GroupBy
**Object that groups together rows of a dataframe based on the value of the passed column.**

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<body>
<header>
<aside>March 3, 2025</aside>
<aside>March 8, 2025</aside>
<a href="https://gto76.github.io" rel="author">Jure Šorn</a>
</header>
@ -2753,8 +2753,9 @@ c <span class="hljs-number">6</span> <span class="hljs-number">7</span>
</code></pre>
<ul>
<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 'parse_dates' and 'index_col' are the same column, we get a DF with DatetimeIndex. Its <code class="python hljs"><span class="hljs-string">'resample("y/m/d/h")'</span></code> method returns a Resampler object that is similar to GroupBy.</strong></li>
<li><strong>Csv functions use the same dialect as standard library's csv module (e.g. <code class="python hljs"><span class="hljs-string">'sep=","'</span></code>).</strong></li>
<li><strong>Read_csv() only parses dates of columns that are listed in 'parse_dates'. It automatically tries to detect the format, but it can be helped with 'date_format' or 'dayfirst' arguments.</strong></li>
<li><strong>We get a dataframe with DatetimeIndex if 'parse_dates' argument includes 'index_col'. Its <code class="python hljs"><span class="hljs-string">'resample("y/m/d/h")'</span></code> method returns Resampler object that is similar to GroupBy.</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>
@ -2942,7 +2943,7 @@ $ deactivate <span class="hljs-comment"># Deactivates the active
<footer>
<aside>March 3, 2025</aside>
<aside>March 8, 2025</aside>
<a href="https://gto76.github.io" rel="author">Jure Šorn</a>
</footer>

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