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<div class="quarto-title">
<h1 class="title">Nested dtypes</h1>
</div>
<div class="quarto-title-meta">
</div>
</header>
<div id="setup-env" class="cell" data-execution_count="2">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># %pip install -r requirements.txt</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<div id="polars-version" class="cell" data-execution_count="3">
<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="op">%</span>pip show Polars <span class="co"># check you Polars version</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>Name: polars
Version: 0.20.19
Summary: Blazingly fast DataFrame library
Home-page:
Author:
Author-email: Ritchie Vink <[email protected]>
License:
Location: /Users/johnros/workspace/polars_demo/.venv/lib/python3.9/site-packages
Requires:
Required-by:
Note: you may need to restart the kernel to use updated packages.</code></pre>
</div>
</div>
<div id="pandas-version" class="cell" data-execution_count="4">
<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="op">%</span>pip show Pandas <span class="co"># check you Pandas version</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>Name: pandas
Version: 2.2.2
Summary: Powerful data structures for data analysis, time series, and statistics
Home-page: https://pandas.pydata.org
Author:
Author-email: The Pandas Development Team <[email protected]>
License: BSD 3-Clause License
Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
All rights reserved.
Copyright (c) 2011-2023, Open source contributors.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Location: /Users/johnros/workspace/polars_demo/.venv/lib/python3.9/site-packages
Requires: numpy, python-dateutil, pytz, tzdata
Required-by: bokeh, category-encoders, great-tables, holoviews, hvplot, mizani, panel, seaborn, statsmodels
Note: you may need to restart the kernel to use updated packages.</code></pre>
</div>
</div>
<div id="preliminaries" class="cell" data-execution_count="5">
<div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> polars <span class="im">as</span> pl</span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a>pl.Config(fmt_str_lengths<span class="op">=</span><span class="dv">50</span>)</span>
<span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> polars.selectors <span class="im">as</span> cs</span>
<span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb6-5"><a href="#cb6-5" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
<span id="cb6-6"><a href="#cb6-6" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> numpy <span class="im">as</span> np</span>
<span id="cb6-7"><a href="#cb6-7" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pyarrow <span class="im">as</span> pa</span>
<span id="cb6-8"><a href="#cb6-8" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.express <span class="im">as</span> px</span>
<span id="cb6-9"><a href="#cb6-9" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> string</span>
<span id="cb6-10"><a href="#cb6-10" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> random</span>
<span id="cb6-11"><a href="#cb6-11" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> os</span>
<span id="cb6-12"><a href="#cb6-12" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> sys</span>
<span id="cb6-13"><a href="#cb6-13" aria-hidden="true" tabindex="-1"></a><span class="op">%</span>matplotlib inline </span>
<span id="cb6-14"><a href="#cb6-14" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> matplotlib.pyplot <span class="im">as</span> plt</span>
<span id="cb6-15"><a href="#cb6-15" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> datetime <span class="im">import</span> datetime</span>
<span id="cb6-16"><a href="#cb6-16" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb6-17"><a href="#cb6-17" aria-hidden="true" tabindex="-1"></a><span class="co"># Following two lines only required to view plotly when rendering from VScode. </span></span>
<span id="cb6-18"><a href="#cb6-18" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.io <span class="im">as</span> pio</span>
<span id="cb6-19"><a href="#cb6-19" aria-hidden="true" tabindex="-1"></a><span class="co"># pio.renderers.default = "plotly_mimetype+notebook_connected+notebook"</span></span>
<span id="cb6-20"><a href="#cb6-20" aria-hidden="true" tabindex="-1"></a>pio.renderers.default <span class="op">=</span> <span class="st">"plotly_mimetype+notebook"</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>What Polars module and dependencies are installed?</p>
<div id="show-versions" class="cell" data-execution_count="6">
<div class="sourceCode cell-code" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>pl.show_versions()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>--------Version info---------
Polars: 0.20.19
Index type: UInt32
Platform: macOS-14.4-arm64-arm-64bit
Python: 3.9.6 (default, Nov 10 2023, 13:38:27)
[Clang 15.0.0 (clang-1500.1.0.2.5)]
----Optional dependencies----
adbc_driver_manager: <not installed>
cloudpickle: <not installed>
connectorx: <not installed>
deltalake: <not installed>
fastexcel: <not installed>
fsspec: 2023.9.0
gevent: <not installed>
hvplot: 0.9.2
matplotlib: 3.6.3
nest_asyncio: 1.5.6
numpy: 1.24.1
openpyxl: <not installed>
pandas: 2.2.2
pyarrow: 15.0.2
pydantic: <not installed>
pyiceberg: <not installed>
pyxlsb: <not installed>
sqlalchemy: 1.4.46
xlsx2csv: <not installed>
xlsxwriter: <not installed></code></pre>
</div>
</div>
<p>How many cores are available for parallelism?</p>
<div id="cell-show-cores" class="cell" data-execution_count="7">
<div class="sourceCode cell-code" id="cb9"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a>pl.thread_pool_size()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="show-cores" class="cell-output cell-output-display" data-execution_count="7">
<pre><code>8</code></pre>
</div>
</div>
<section id="introduction" class="level1">
<h1>Introduction</h1>
<p>Recall the nested dtypes:</p>
<ol type="1">
<li>Polars Struct: Like a Python dict within a cell; Multiple named elements.</li>
<li>Polars List: Similar to a Python list within a cell; Multiple unnamed elements. Unlike the Python list, in a Polars list, all elements must have the same dtype.</li>
<li>Polars Array: Like a Polars list, but with a fixed length for all cells in the column.</li>
</ol>
</section>
<section id="sec-list" class="level1">
<h1>Polars List</h1>
<section id="making-a-polars-list" class="level2">
<h2 class="anchored" data-anchor-id="making-a-polars-list">Making a Polars List</h2>
<p>Make a Polars list from a Python list.</p>
<div id="cell-make-list" class="cell" data-execution_count="8">
<div class="sourceCode cell-code" id="cb11"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a>pl.DataFrame(</span>
<span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a> {</span>
<span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a> <span class="st">"a"</span>: [[<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>], [<span class="dv">4</span>, <span class="dv">5</span>, <span class="dv">6</span>], [<span class="dv">7</span>, <span class="dv">8</span>, <span class="dv">9</span>]],</span>
<span id="cb11-4"><a href="#cb11-4" aria-hidden="true" tabindex="-1"></a> <span class="st">"b"</span>: [<span class="st">"a"</span>, <span class="st">"b"</span>, <span class="st">"c"</span>]</span>
<span id="cb11-5"><a href="#cb11-5" aria-hidden="true" tabindex="-1"></a> }</span>
<span id="cb11-6"><a href="#cb11-6" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="make-list" class="cell-output cell-output-display" data-execution_count="8">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (3, 2)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">a</th>
<th data-quarto-table-cell-role="th">b</th>
</tr>
<tr class="odd">
<th>list[i64]</th>
<th>str</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>[1, 2, 3]</td>
<td>"a"</td>
</tr>
<tr class="even">
<td>[4, 5, 6]</td>
<td>"b"</td>
</tr>
<tr class="odd">
<td>[7, 8, 9]</td>
<td>"c"</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>Things to note:</p>
<ul>
<li><code>a</code> is not a Python list, rather, it is a Polars list. There are differences between the two. For instance, all elements in a Polars list must have the same dtype. Also, the Polars list is a columnar data structure, which is more efficient for certain operations. Finally, the Polars list is a first-class citizen in the Polars API, with its own methods and functions.</li>
<li>Can a Polars list hold a polars list? Yes. See the next example.</li>
</ul>
<p>Make a Polars list of Polars lists:</p>
<div id="cell-make-list-of-list" class="cell" data-execution_count="9">
<div class="sourceCode cell-code" id="cb12"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a>pl.DataFrame(</span>
<span id="cb12-2"><a href="#cb12-2" aria-hidden="true" tabindex="-1"></a> {</span>
<span id="cb12-3"><a href="#cb12-3" aria-hidden="true" tabindex="-1"></a> <span class="st">"a"</span>: [[[<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>], [<span class="dv">4</span>, <span class="dv">5</span>, <span class="dv">6</span>], [<span class="dv">7</span>, <span class="dv">8</span>, <span class="dv">9</span>]], [[<span class="dv">10</span>, <span class="dv">11</span>, <span class="dv">12</span>], [<span class="dv">13</span>, <span class="dv">14</span>, <span class="dv">15</span>], [<span class="dv">16</span>, <span class="dv">17</span>, <span class="dv">18</span>]]],</span>
<span id="cb12-4"><a href="#cb12-4" aria-hidden="true" tabindex="-1"></a> <span class="st">"b"</span>: [<span class="st">"a"</span>, <span class="st">"b"</span>]</span>
<span id="cb12-5"><a href="#cb12-5" aria-hidden="true" tabindex="-1"></a> }</span>
<span id="cb12-6"><a href="#cb12-6" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="make-list-of-list" class="cell-output cell-output-display" data-execution_count="9">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (2, 2)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">a</th>
<th data-quarto-table-cell-role="th">b</th>
</tr>
<tr class="odd">
<th>list[list[i64]]</th>
<th>str</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>[[1, 2, 3], [4, 5, 6], [7, 8, 9]]</td>
<td>"a"</td>
</tr>
<tr class="even">
<td>[[10, 11, 12], [13, 14, 15], [16, 17, 18]]</td>
<td>"b"</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>More often you will not make a Polars list directly, but rather you will create one from a Polars DataFrame:</p>
<ol type="1">
<li>When grouping without aggregation.</li>
<li>When wrapping a bunch of columns with <code>pl.concat_list()</code>.</li>
<li>When “imploding” (aka “collapsing”) an <code>pl.Expr()</code>.</li>
</ol>
<p>List from aggregation:</p>
<div id="cell-list-from-aggregation" class="cell" data-execution_count="10">
<div class="sourceCode cell-code" id="cb13"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a>df <span class="op">=</span> pl.DataFrame(</span>
<span id="cb13-2"><a href="#cb13-2" aria-hidden="true" tabindex="-1"></a> {</span>
<span id="cb13-3"><a href="#cb13-3" aria-hidden="true" tabindex="-1"></a> <span class="st">"a"</span>: [<span class="dv">1</span>, <span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">2</span>, <span class="dv">3</span>, <span class="dv">3</span>],</span>
<span id="cb13-4"><a href="#cb13-4" aria-hidden="true" tabindex="-1"></a> <span class="st">"b"</span>: [<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>, <span class="dv">4</span>, <span class="dv">5</span>, <span class="dv">6</span>]</span>
<span id="cb13-5"><a href="#cb13-5" aria-hidden="true" tabindex="-1"></a> }</span>
<span id="cb13-6"><a href="#cb13-6" aria-hidden="true" tabindex="-1"></a>)</span>
<span id="cb13-7"><a href="#cb13-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb13-8"><a href="#cb13-8" aria-hidden="true" tabindex="-1"></a>df.group_by(<span class="st">"a"</span>).agg(pl.col(<span class="st">"b"</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="list-from-aggregation" class="cell-output cell-output-display" data-execution_count="10">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (3, 2)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">a</th>
<th data-quarto-table-cell-role="th">b</th>
</tr>
<tr class="odd">
<th>i64</th>
<th>list[i64]</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>1</td>
<td>[1, 2]</td>
</tr>
<tr class="even">
<td>2</td>
<td>[3, 4]</td>
</tr>
<tr class="odd">
<td>3</td>
<td>[5, 6]</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>List from concatenation of pl.Exprs():</p>
<div id="cell-list-from-concatenation" class="cell" data-execution_count="11">
<div class="sourceCode cell-code" id="cb14"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb14-1"><a href="#cb14-1" aria-hidden="true" tabindex="-1"></a>df.select(pl.concat_list([pl.col(<span class="st">"a"</span>), pl.col(<span class="st">"b"</span>)]))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="list-from-concatenation" class="cell-output cell-output-display" data-execution_count="11">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (6, 1)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">a</th>
</tr>
<tr class="odd">
<th>list[i64]</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>[1, 1]</td>
</tr>
<tr class="even">
<td>[1, 2]</td>
</tr>
<tr class="odd">
<td>[2, 3]</td>
</tr>
<tr class="even">
<td>[2, 4]</td>
</tr>
<tr class="odd">
<td>[3, 5]</td>
</tr>
<tr class="even">
<td>[3, 6]</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>List from concatenation of pl.Lists:</p>
<div id="1eb83c64" class="cell" data-execution_count="12">
<div class="sourceCode cell-code" id="cb15"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a>(</span>
<span id="cb15-2"><a href="#cb15-2" aria-hidden="true" tabindex="-1"></a> df</span>
<span id="cb15-3"><a href="#cb15-3" aria-hidden="true" tabindex="-1"></a> .select(</span>
<span id="cb15-4"><a href="#cb15-4" aria-hidden="true" tabindex="-1"></a> pl.concat_list([pl.col(<span class="st">"a"</span>), pl.col(<span class="st">"b"</span>)]).alias(<span class="st">'ab'</span>)</span>
<span id="cb15-5"><a href="#cb15-5" aria-hidden="true" tabindex="-1"></a> )</span>
<span id="cb15-6"><a href="#cb15-6" aria-hidden="true" tabindex="-1"></a> .with_columns(pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.concat(<span class="st">'ab'</span>))</span>
<span id="cb15-7"><a href="#cb15-7" aria-hidden="true" tabindex="-1"></a> .to_pandas()</span>
<span id="cb15-8"><a href="#cb15-8" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-display" data-execution_count="12">
<div>
<div>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th"></th>
<th data-quarto-table-cell-role="th">ab</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td data-quarto-table-cell-role="th">0</td>
<td>[1, 1, 1, 1]</td>
</tr>
<tr class="even">
<td data-quarto-table-cell-role="th">1</td>
<td>[1, 2, 1, 2]</td>
</tr>
<tr class="odd">
<td data-quarto-table-cell-role="th">2</td>
<td>[2, 3, 2, 3]</td>
</tr>
<tr class="even">
<td data-quarto-table-cell-role="th">3</td>
<td>[2, 4, 2, 4]</td>
</tr>
<tr class="odd">
<td data-quarto-table-cell-role="th">4</td>
<td>[3, 5, 3, 5]</td>
</tr>
<tr class="even">
<td data-quarto-table-cell-role="th">5</td>
<td>[3, 6, 3, 6]</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>List from imploding an <code>pl.Expr()</code>:</p>
<div id="cell-list-from-imploding" class="cell" data-execution_count="13">
<div class="sourceCode cell-code" id="cb16"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb16-1"><a href="#cb16-1" aria-hidden="true" tabindex="-1"></a>df.with_columns(pl.col(<span class="st">"b"</span>).implode())</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="list-from-imploding" class="cell-output cell-output-display" data-execution_count="13">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (6, 2)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">a</th>
<th data-quarto-table-cell-role="th">b</th>
</tr>
<tr class="odd">
<th>i64</th>
<th>list[i64]</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>1</td>
<td>[1, 2, … 6]</td>
</tr>
<tr class="even">
<td>1</td>
<td>[1, 2, … 6]</td>
</tr>
<tr class="odd">
<td>2</td>
<td>[1, 2, … 6]</td>
</tr>
<tr class="even">
<td>2</td>
<td>[1, 2, … 6]</td>
</tr>
<tr class="odd">
<td>3</td>
<td>[1, 2, … 6]</td>
</tr>
<tr class="even">
<td>3</td>
<td>[1, 2, … 6]</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>Implode within group:</p>
<div id="cell-implode-within-group" class="cell" data-execution_count="14">
<div class="sourceCode cell-code" id="cb17"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a>df.group_by(<span class="st">"a"</span>).agg(pl.col(<span class="st">"b"</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="implode-within-group" class="cell-output cell-output-display" data-execution_count="14">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (3, 2)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">a</th>
<th data-quarto-table-cell-role="th">b</th>
</tr>
<tr class="odd">
<th>i64</th>
<th>list[i64]</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>3</td>
<td>[5, 6]</td>
</tr>
<tr class="even">
<td>2</td>
<td>[3, 4]</td>
</tr>
<tr class="odd">
<td>1</td>
<td>[1, 2]</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>Implode over:</p>
<div id="implode-over" class="cell" data-execution_count="15">
<div class="sourceCode cell-code" id="cb18"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a>df.with_columns(pl.col(<span class="st">"b"</span>).over(<span class="st">"a"</span>)) <span class="co"># no good</span></span>
<span id="cb18-2"><a href="#cb18-2" aria-hidden="true" tabindex="-1"></a>df.with_columns(pl.col(<span class="st">"b"</span>).implode().over(<span class="st">"a"</span>)) <span class="co"># no good</span></span>
<span id="cb18-3"><a href="#cb18-3" aria-hidden="true" tabindex="-1"></a>df.with_columns(pl.concat_list(<span class="st">'b'</span>).over(<span class="st">"a"</span>)) <span class="co"># no good</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<div id="faed5f3a" class="cell" data-execution_count="16">
<div class="sourceCode cell-code" id="cb19"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb19-1"><a href="#cb19-1" aria-hidden="true" tabindex="-1"></a>df.with_columns(pl.col(<span class="st">"b"</span>).over(<span class="st">"a"</span>, mapping_strategy<span class="op">=</span><span class="st">"join"</span>)) <span class="co"># good!</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-display" data-execution_count="15">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (6, 2)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">a</th>
<th data-quarto-table-cell-role="th">b</th>
</tr>
<tr class="odd">
<th>i64</th>
<th>list[i64]</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>1</td>
<td>[1, 2]</td>
</tr>
<tr class="even">
<td>1</td>
<td>[1, 2]</td>
</tr>
<tr class="odd">
<td>2</td>
<td>[3, 4]</td>
</tr>
<tr class="even">
<td>2</td>
<td>[3, 4]</td>
</tr>
<tr class="odd">
<td>3</td>
<td>[5, 6]</td>
</tr>
<tr class="even">
<td>3</td>
<td>[5, 6]</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>See <a href="https://github.com/pola-rs/polars/pull/6487">here</a> for more context.</p>
<section id="more-on-.overmapping_strategy..." class="level3">
<h3 class="anchored" data-anchor-id="more-on-.overmapping_strategy...">More on <code>.over(mapping_strategy=...)</code></h3>
<p>TODO</p>
</section>
</section>
<section id="operating-on-list-elements" class="level2">
<h2 class="anchored" data-anchor-id="operating-on-list-elements">Operating on List Elements</h2>
<p>The most general way is to use <code>list.eval(pl.element())</code>:</p>
<div id="cell-list-eval-element" class="cell" data-execution_count="17">
<div class="sourceCode cell-code" id="cb20"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a>df_with_list <span class="op">=</span> df.with_columns(pl.concat_list([pl.col(<span class="st">"a"</span>), pl.col(<span class="st">"b"</span>)]).alias(<span class="st">'ab'</span>))</span>
<span id="cb20-2"><a href="#cb20-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb20-3"><a href="#cb20-3" aria-hidden="true" tabindex="-1"></a>(</span>
<span id="cb20-4"><a href="#cb20-4" aria-hidden="true" tabindex="-1"></a> df_with_list</span>
<span id="cb20-5"><a href="#cb20-5" aria-hidden="true" tabindex="-1"></a> .select(</span>
<span id="cb20-6"><a href="#cb20-6" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.<span class="bu">eval</span>(pl.element().add(<span class="dv">1000</span>))</span>
<span id="cb20-7"><a href="#cb20-7" aria-hidden="true" tabindex="-1"></a> )</span>
<span id="cb20-8"><a href="#cb20-8" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="list-eval-element" class="cell-output cell-output-display" data-execution_count="16">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (6, 1)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">ab</th>
</tr>
<tr class="odd">
<th>list[i64]</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>[1001, 1001]</td>
</tr>
<tr class="even">
<td>[1001, 1002]</td>
</tr>
<tr class="odd">
<td>[1002, 1003]</td>
</tr>
<tr class="even">
<td>[1002, 1004]</td>
</tr>
<tr class="odd">
<td>[1003, 1005]</td>
</tr>
<tr class="even">
<td>[1003, 1006]</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>Things to note:</p>
<ul>
<li><code>.eval()</code> belongs to the <code>.list</code> namespace.</li>
<li><code>pl.element()</code> is a selector that selects the elements of the list. It has almost all the methods available to <code>pl.col()</code>.</li>
</ul>
<div id="list-eval-element-methods" class="cell" data-execution_count="18">
<div class="sourceCode cell-code" id="cb21"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="bu">dir</span>(pl.element()))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>['__abs__', '__add__', '__and__', '__annotations__', '__array_ufunc__', '__bool__', '__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__floordiv__', '__format__', '__ge__', '__getattribute__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__invert__', '__le__', '__lt__', '__mod__', '__module__', '__mul__', '__ne__', '__neg__', '__new__', '__or__', '__pos__', '__pow__', '__radd__', '__rand__', '__reduce__', '__reduce_ex__', '__repr__', '__rfloordiv__', '__rmod__', '__rmul__', '__ror__', '__rpow__', '__rsub__', '__rtruediv__', '__rxor__', '__setattr__', '__setstate__', '__sizeof__', '__str__', '__sub__', '__subclasshook__', '__truediv__', '__weakref__', '__xor__', '_accessors', '_from_pyexpr', '_map_batches_wrapper', '_pyexpr', '_register_plugin', '_repr_html_', 'abs', 'add', 'agg_groups', 'alias', 'all', 'and_', 'any', 'append', 'apply', 'approx_n_unique', 'arccos', 'arccosh', 'arcsin', 'arcsinh', 'arctan', 'arctanh', 'arg_max', 'arg_min', 'arg_sort', 'arg_true', 'arg_unique', 'arr', 'backward_fill', 'bin', 'bottom_k', 'cast', 'cat', 'cbrt', 'ceil', 'clip', 'clip_max', 'clip_min', 'cos', 'cosh', 'cot', 'count', 'cum_count', 'cum_max', 'cum_min', 'cum_prod', 'cum_sum', 'cumcount', 'cummax', 'cummin', 'cumprod', 'cumsum', 'cumulative_eval', 'cut', 'degrees', 'deserialize', 'diff', 'dot', 'drop_nans', 'drop_nulls', 'dt', 'entropy', 'eq', 'eq_missing', 'ewm_mean', 'ewm_std', 'ewm_var', 'exclude', 'exp', 'explode', 'extend_constant', 'fill_nan', 'fill_null', 'filter', 'first', 'flatten', 'floor', 'floordiv', 'forward_fill', 'from_json', 'gather', 'gather_every', 'ge', 'get', 'gt', 'hash', 'head', 'hist', 'implode', 'inspect', 'interpolate', 'is_between', 'is_duplicated', 'is_finite', 'is_first', 'is_first_distinct', 'is_in', 'is_infinite', 'is_last', 'is_last_distinct', 'is_nan', 'is_not', 'is_not_nan', 'is_not_null', 'is_null', 'is_unique', 'keep_name', 'kurtosis', 'last', 'le', 'len', 'limit', 'list', 'log', 'log10', 'log1p', 'lower_bound', 'lt', 'map', 'map_alias', 'map_batches', 'map_dict', 'map_elements', 'max', 'mean', 'median', 'meta', 'min', 'mod', 'mode', 'mul', 'n_unique', 'name', 'nan_max', 'nan_min', 'ne', 'ne_missing', 'neg', 'not_', 'null_count', 'or_', 'over', 'pct_change', 'peak_max', 'peak_min', 'pipe', 'pow', 'prefix', 'product', 'qcut', 'quantile', 'radians', 'rank', 'rechunk', 'register_plugin', 'reinterpret', 'repeat_by', 'replace', 'reshape', 'reverse', 'rle', 'rle_id', 'rolling', 'rolling_apply', 'rolling_map', 'rolling_max', 'rolling_mean', 'rolling_median', 'rolling_min', 'rolling_quantile', 'rolling_skew', 'rolling_std', 'rolling_sum', 'rolling_var', 'round', 'round_sig_figs', 'sample', 'search_sorted', 'set_sorted', 'shift', 'shift_and_fill', 'shrink_dtype', 'shuffle', 'sign', 'sin', 'sinh', 'skew', 'slice', 'sort', 'sort_by', 'sqrt', 'std', 'str', 'struct', 'sub', 'suffix', 'sum', 'tail', 'take', 'take_every', 'tan', 'tanh', 'to_physical', 'top_k', 'truediv', 'unique', 'unique_counts', 'upper_bound', 'value_counts', 'var', 'where', 'xor']</code></pre>
</div>
</div>
</section>
<section id="list-methods" class="level2">
<h2 class="anchored" data-anchor-id="list-methods">List Methods</h2>
<p><code>.list.eval(pl.element())</code> will operate one element at a time. If you want to operate on the list as a whole, you can wither use existing <a href="https://docs.pola.rs/py-polars/html/reference/expressions/list.html">list methods</a>, or use <code>pl.col()</code> methods, after exploding the list (see <a href="#sec-list-explode" class="quarto-xref">Section 2.4</a>).</p>
<p>We now demonstrate some of the list methods.</p>
<section id="selecting-elements" class="level3">
<h3 class="anchored" data-anchor-id="selecting-elements">Selecting Elements</h3>
<p>Get, Gather, Slice, Gather_Every</p>
<div id="cell-list-get-and-gather" class="cell" data-execution_count="19">
<div class="sourceCode cell-code" id="cb23"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb23-1"><a href="#cb23-1" aria-hidden="true" tabindex="-1"></a>(</span>
<span id="cb23-2"><a href="#cb23-2" aria-hidden="true" tabindex="-1"></a> df_with_list.select(</span>
<span id="cb23-3"><a href="#cb23-3" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>),</span>
<span id="cb23-4"><a href="#cb23-4" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.get(<span class="dv">0</span>).alias(<span class="st">'get_1'</span>), </span>
<span id="cb23-5"><a href="#cb23-5" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.gather([<span class="dv">0</span>]).alias(<span class="st">'gather_1'</span>), <span class="co"># returns a list</span></span>
<span id="cb23-6"><a href="#cb23-6" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.<span class="bu">slice</span>(<span class="dv">0</span>,<span class="dv">1</span>).alias(<span class="st">'slice_1'</span>), <span class="co"># returns a list</span></span>
<span id="cb23-7"><a href="#cb23-7" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.gather([<span class="dv">0</span>, <span class="dv">1</span>]).alias(<span class="st">'gather_2'</span>),</span>
<span id="cb23-8"><a href="#cb23-8" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.<span class="bu">slice</span>(<span class="dv">0</span>,<span class="dv">2</span>).alias(<span class="st">'slice_2'</span>),</span>
<span id="cb23-9"><a href="#cb23-9" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.gather_every(<span class="dv">2</span>).alias(<span class="st">'gather_every_2'</span>),</span>
<span id="cb23-10"><a href="#cb23-10" aria-hidden="true" tabindex="-1"></a> )</span>
<span id="cb23-11"><a href="#cb23-11" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="list-get-and-gather" class="cell-output cell-output-display" data-execution_count="18">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (6, 7)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">ab</th>
<th data-quarto-table-cell-role="th">get_1</th>
<th data-quarto-table-cell-role="th">gather_1</th>
<th data-quarto-table-cell-role="th">slice_1</th>
<th data-quarto-table-cell-role="th">gather_2</th>
<th data-quarto-table-cell-role="th">slice_2</th>
<th data-quarto-table-cell-role="th">gather_every_2</th>
</tr>
<tr class="odd">
<th>list[i64]</th>
<th>i64</th>
<th>list[i64]</th>
<th>list[i64]</th>
<th>list[i64]</th>
<th>list[i64]</th>
<th>list[i64]</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>[1, 1]</td>
<td>1</td>
<td>[1]</td>
<td>[1]</td>
<td>[1, 1]</td>
<td>[1, 1]</td>
<td>[1]</td>
</tr>
<tr class="even">
<td>[1, 2]</td>
<td>1</td>
<td>[1]</td>
<td>[1]</td>
<td>[1, 2]</td>
<td>[1, 2]</td>
<td>[1]</td>
</tr>
<tr class="odd">
<td>[2, 3]</td>
<td>2</td>
<td>[2]</td>
<td>[2]</td>
<td>[2, 3]</td>
<td>[2, 3]</td>
<td>[2]</td>
</tr>
<tr class="even">
<td>[2, 4]</td>
<td>2</td>
<td>[2]</td>
<td>[2]</td>
<td>[2, 4]</td>
<td>[2, 4]</td>
<td>[2]</td>
</tr>
<tr class="odd">
<td>[3, 5]</td>
<td>3</td>
<td>[3]</td>
<td>[3]</td>
<td>[3, 5]</td>
<td>[3, 5]</td>
<td>[3]</td>
</tr>
<tr class="even">
<td>[3, 6]</td>
<td>3</td>
<td>[3]</td>
<td>[3]</td>
<td>[3, 6]</td>
<td>[3, 6]</td>
<td>[3]</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>First, Head, Last, Tail</p>
<div id="cell-list-methods" class="cell" data-execution_count="20">
<div class="sourceCode cell-code" id="cb24"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb24-1"><a href="#cb24-1" aria-hidden="true" tabindex="-1"></a>(</span>
<span id="cb24-2"><a href="#cb24-2" aria-hidden="true" tabindex="-1"></a> df_with_list.select(</span>
<span id="cb24-3"><a href="#cb24-3" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>),</span>
<span id="cb24-4"><a href="#cb24-4" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.get(<span class="dv">1</span>).alias(<span class="st">'first_1'</span>),</span>
<span id="cb24-5"><a href="#cb24-5" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.first().alias(<span class="st">'first_2'</span>),</span>
<span id="cb24-6"><a href="#cb24-6" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.head(<span class="dv">1</span>).alias(<span class="st">'first_5'</span>), <span class="co"># returns a list</span></span>
<span id="cb24-7"><a href="#cb24-7" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.last().alias(<span class="st">'last_2'</span>), </span>
<span id="cb24-8"><a href="#cb24-8" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.tail(<span class="dv">1</span>).alias(<span class="st">'last_1'</span>), <span class="co"># returns a list</span></span>
<span id="cb24-9"><a href="#cb24-9" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.tail(<span class="dv">1</span>).<span class="bu">list</span>.first().alias(<span class="st">'last_3'</span>),</span>
<span id="cb24-10"><a href="#cb24-10" aria-hidden="true" tabindex="-1"></a> )</span>
<span id="cb24-11"><a href="#cb24-11" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="list-methods" class="cell-output cell-output-display" data-execution_count="19">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (6, 7)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">ab</th>
<th data-quarto-table-cell-role="th">first_1</th>
<th data-quarto-table-cell-role="th">first_2</th>
<th data-quarto-table-cell-role="th">first_5</th>
<th data-quarto-table-cell-role="th">last_2</th>
<th data-quarto-table-cell-role="th">last_1</th>
<th data-quarto-table-cell-role="th">last_3</th>
</tr>
<tr class="odd">
<th>list[i64]</th>
<th>i64</th>
<th>i64</th>
<th>list[i64]</th>
<th>i64</th>
<th>list[i64]</th>
<th>i64</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>[1, 1]</td>
<td>1</td>
<td>1</td>
<td>[1]</td>
<td>1</td>
<td>[1]</td>
<td>1</td>
</tr>
<tr class="even">
<td>[1, 2]</td>
<td>2</td>
<td>1</td>
<td>[1]</td>
<td>2</td>
<td>[2]</td>
<td>2</td>
</tr>
<tr class="odd">
<td>[2, 3]</td>
<td>3</td>
<td>2</td>
<td>[2]</td>
<td>3</td>
<td>[3]</td>
<td>3</td>
</tr>
<tr class="even">
<td>[2, 4]</td>
<td>4</td>
<td>2</td>
<td>[2]</td>
<td>4</td>
<td>[4]</td>
<td>4</td>
</tr>
<tr class="odd">
<td>[3, 5]</td>
<td>5</td>
<td>3</td>
<td>[3]</td>
<td>5</td>
<td>[5]</td>
<td>5</td>
</tr>
<tr class="even">
<td>[3, 6]</td>
<td>6</td>
<td>3</td>
<td>[3]</td>
<td>6</td>
<td>[6]</td>
<td>6</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
<p>Shift</p>
<div id="cell-list-shift" class="cell" data-execution_count="21">
<div class="sourceCode cell-code" id="cb25"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb25-1"><a href="#cb25-1" aria-hidden="true" tabindex="-1"></a>(</span>
<span id="cb25-2"><a href="#cb25-2" aria-hidden="true" tabindex="-1"></a> df_with_list.select(</span>
<span id="cb25-3"><a href="#cb25-3" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>),</span>
<span id="cb25-4"><a href="#cb25-4" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.shift(<span class="dv">1</span>).alias(<span class="st">'shift_1'</span>),</span>
<span id="cb25-5"><a href="#cb25-5" aria-hidden="true" tabindex="-1"></a> pl.col(<span class="st">'ab'</span>).<span class="bu">list</span>.shift(<span class="op">-</span><span class="dv">1</span>).alias(<span class="st">'shift_-1'</span>),</span>
<span id="cb25-6"><a href="#cb25-6" aria-hidden="true" tabindex="-1"></a> )</span>
<span id="cb25-7"><a href="#cb25-7" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div id="list-shift" class="cell-output cell-output-display" data-execution_count="20">
<div>
<div><style>
.dataframe > thead > tr,
.dataframe > tbody > tr {
text-align: right;
white-space: pre-wrap;
}
</style>
<small>shape: (6, 3)</small>
<table class="dataframe table table-sm table-striped small" data-quarto-postprocess="true" data-border="1">
<thead>
<tr class="header">
<th data-quarto-table-cell-role="th">ab</th>
<th data-quarto-table-cell-role="th">shift_1</th>
<th data-quarto-table-cell-role="th">shift_-1</th>
</tr>
<tr class="odd">
<th>list[i64]</th>
<th>list[i64]</th>
<th>list[i64]</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>[1, 1]</td>
<td>[null, 1]</td>
<td>[1, null]</td>
</tr>
<tr class="even">
<td>[1, 2]</td>
<td>[null, 1]</td>
<td>[2, null]</td>
</tr>
<tr class="odd">
<td>[2, 3]</td>
<td>[null, 2]</td>
<td>[3, null]</td>
</tr>
<tr class="even">
<td>[2, 4]</td>
<td>[null, 2]</td>
<td>[4, null]</td>
</tr>
<tr class="odd">
<td>[3, 5]</td>
<td>[null, 3]</td>