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<!DOCTYPE html>
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<title>plotly.data package — 6.6.0 documentation</title>
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<div class="section" id="module-plotly.data">
<span id="plotly-data-package"></span><h1>plotly.data package<a class="headerlink" href="#module-plotly.data" title="Permalink to this headline">¶</a></h1>
<p>Built-in datasets for demonstration, educational and test purposes.</p>
<dl class="py function">
<dt id="plotly.data.carshare">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">carshare</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.carshare" title="Permalink to this definition">¶</a></dt>
<dd><p>Each row represents the availability of car-sharing services near the centroid of a zone
in Montreal over a month-long period.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe` with 249 rows and the following columns:
<code class="docutils literal notranslate"><span class="pre">['centroid_lat',</span> <span class="pre">'centroid_lon',</span> <span class="pre">'car_hours',</span> <span class="pre">'peak_hour']</span></code>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.election">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">election</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.election" title="Permalink to this definition">¶</a></dt>
<dd><p>Each row represents voting results for an electoral district in the 2013 Montreal
mayoral election.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe with 58 rows and the following columns:
<code class="docutils literal notranslate"><span class="pre">['district',</span> <span class="pre">'Coderre',</span> <span class="pre">'Bergeron',</span> <span class="pre">'Joly',</span> <span class="pre">'total',</span> <span class="pre">'winner',</span> <span class="pre">'result',</span> <span class="pre">'district_id']</span></code>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.election_geojson">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">election_geojson</span></code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.election_geojson" title="Permalink to this definition">¶</a></dt>
<dd><p>Each feature represents an electoral district in the 2013 Montreal mayoral election.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p><ul class="simple">
<li><p>A GeoJSON-formatted <code class="docutils literal notranslate"><span class="pre">dict</span></code> with 58 polygon or multi-polygon features whose <code class="docutils literal notranslate"><span class="pre">id</span></code></p></li>
<li><p>is an electoral district numerical ID and whose <code class="docutils literal notranslate"><span class="pre">district</span></code> property is the ID and</p></li>
<li><p><em>district name.</em></p></li>
</ul>
</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.experiment">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">experiment</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">indexed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.experiment" title="Permalink to this definition">¶</a></dt>
<dd><p>Each row in this wide dataset represents the results of 100 simulated participants
on three hypothetical experiments, along with their gender and control/treatment group.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>indexed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – If True, then the index is named “participant”.
Applicable only if <code class="docutils literal notranslate"><span class="pre">return_type='pandas'</span></code></p></li>
<li><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe with 100 rows and the following columns:
<code class="docutils literal notranslate"><span class="pre">['experiment_1',</span> <span class="pre">'experiment_2',</span> <span class="pre">'experiment_3',</span> <span class="pre">'gender',</span> <span class="pre">'group']</span></code>.
If <code class="docutils literal notranslate"><span class="pre">indexed</span></code> is True, the data frame index is named “participant”</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.gapminder">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">gapminder</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetimes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">centroids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">year</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pretty_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.gapminder" title="Permalink to this definition">¶</a></dt>
<dd><p>Each row represents a country on a given year.</p>
<p><a class="reference external" href="https://www.gapminder.org/data/">https://www.gapminder.org/data/</a></p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>datetimes</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – Whether or not ‘year’ column will converted to datetime type</p></li>
<li><p><strong>centroids</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – If True, [‘centroid_lat’, ‘centroid_lon’] columns are added</p></li>
<li><p><strong>year</strong> (<em>int | None</em>) – If provided, the dataset will be filtered for that year</p></li>
<li><p><strong>pretty_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – If True, prettifies the column names</p></li>
<li><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p><p>Dataframe with 1704 rows and the following columns:
<code class="docutils literal notranslate"><span class="pre">['country',</span> <span class="pre">'continent',</span> <span class="pre">'year',</span> <span class="pre">'lifeExp',</span> <span class="pre">'pop',</span> <span class="pre">'gdpPercap',</span>
<span class="pre">'iso_alpha',</span> <span class="pre">'iso_num']</span></code>.</p>
<p>If <code class="docutils literal notranslate"><span class="pre">datetimes</span></code> is True, the ‘year’ column will be a datetime column
If <code class="docutils literal notranslate"><span class="pre">centroids</span></code> is True, two new columns are added: [‘centroid_lat’, ‘centroid_lon’]
If <code class="docutils literal notranslate"><span class="pre">year</span></code> is an integer, the dataset will be filtered for that year</p>
</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.iris">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">iris</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.iris" title="Permalink to this definition">¶</a></dt>
<dd><p>Each row represents a flower.</p>
<p><a class="reference external" href="https://en.wikipedia.org/wiki/Iris_flower_data_set">https://en.wikipedia.org/wiki/Iris_flower_data_set</a></p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe with 150 rows and the following columns:
<code class="docutils literal notranslate"><span class="pre">['sepal_length',</span> <span class="pre">'sepal_width',</span> <span class="pre">'petal_length',</span> <span class="pre">'petal_width',</span> <span class="pre">'species',</span> <span class="pre">'species_id']</span></code>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.medals_long">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">medals_long</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">indexed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.medals_long" title="Permalink to this definition">¶</a></dt>
<dd><p>This dataset represents the medal table for Olympic Short Track Speed Skating for the
top three nations as of 2020.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>indexed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – Whether or not the ‘nation’ column is used as the index.
Applicable only if <code class="docutils literal notranslate"><span class="pre">return_type='pandas'</span></code></p></li>
<li><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe with 9 rows and the following columns: <code class="docutils literal notranslate"><span class="pre">['nation',</span> <span class="pre">'medal',</span> <span class="pre">'count']</span></code>.
If <code class="docutils literal notranslate"><span class="pre">indexed</span></code> is True, the ‘nation’ column is used as the index.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.medals_wide">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">medals_wide</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">indexed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.medals_wide" title="Permalink to this definition">¶</a></dt>
<dd><p>This dataset represents the medal table for Olympic Short Track Speed Skating for the
top three nations as of 2020.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>indexed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – Whether or not the ‘nation’ column is used as the index and the column index
is named ‘medal’. Applicable only if <code class="docutils literal notranslate"><span class="pre">return_type='pandas'</span></code></p></li>
<li><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe with 3 rows and the following columns:
<code class="docutils literal notranslate"><span class="pre">['nation',</span> <span class="pre">'gold',</span> <span class="pre">'silver',</span> <span class="pre">'bronze']</span></code>.
If <code class="docutils literal notranslate"><span class="pre">indexed</span></code> is True, the ‘nation’ column is used as the index and the column index
is named ‘medal’</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.stocks">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">stocks</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">indexed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datetimes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.stocks" title="Permalink to this definition">¶</a></dt>
<dd><p>Each row in this wide dataset represents closing prices from 6 tech stocks in 2018/2019.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>indexed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – Whether or not the ‘date’ column is used as the index and the column index
is named ‘company’. Applicable only if <code class="docutils literal notranslate"><span class="pre">return_type='pandas'</span></code></p></li>
<li><p><strong>datetimes</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – Whether or not the ‘date’ column will be of datetime type</p></li>
<li><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe with 100 rows and the following columns:
<code class="docutils literal notranslate"><span class="pre">['date',</span> <span class="pre">'GOOG',</span> <span class="pre">'AAPL',</span> <span class="pre">'AMZN',</span> <span class="pre">'FB',</span> <span class="pre">'NFLX',</span> <span class="pre">'MSFT']</span></code>.
If <code class="docutils literal notranslate"><span class="pre">indexed</span></code> is True, the ‘date’ column is used as the index and the column index
is named ‘company’
If <code class="docutils literal notranslate"><span class="pre">datetimes</span></code> is True, the ‘date’ column will be a datetime column</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.tips">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">tips</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pretty_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.tips" title="Permalink to this definition">¶</a></dt>
<dd><p>Each row represents a restaurant bill.</p>
<p><a class="reference external" href="https://vincentarelbundock.github.io/Rdatasets/doc/reshape2/tips.html">https://vincentarelbundock.github.io/Rdatasets/doc/reshape2/tips.html</a></p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>pretty_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – If True, prettifies the column names</p></li>
<li><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe with 244 rows and the following columns:
<code class="docutils literal notranslate"><span class="pre">['total_bill',</span> <span class="pre">'tip',</span> <span class="pre">'sex',</span> <span class="pre">'smoker',</span> <span class="pre">'day',</span> <span class="pre">'time',</span> <span class="pre">'size']</span></code>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="plotly.data.wind">
<code class="sig-prename descclassname"><span class="pre">plotly.data.</span></code><code class="sig-name descname"><span class="pre">wind</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">return_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pandas'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#plotly.data.wind" title="Permalink to this definition">¶</a></dt>
<dd><p>Each row represents a level of wind intensity in a cardinal direction, and its frequency.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>return_type</strong> (<em>{'pandas'</em><em>, </em><em>'polars'</em><em>, </em><em>'pyarrow'</em><em>, </em><em>'modin'</em><em>, </em><em>'cudf'}</em>) – Type of the resulting dataframe</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe with 128 rows and the following columns:
<code class="docutils literal notranslate"><span class="pre">['direction',</span> <span class="pre">'strength',</span> <span class="pre">'frequency']</span></code>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dataframe of <code class="docutils literal notranslate"><span class="pre">return_type</span></code> type</p>
</dd>
</dl>
</dd></dl>
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