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<title>plotly.data package — 4.6.0 documentation</title>
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<div class="section" id="plotly-data-package">
<h1>plotly.data package<a class="headerlink" href="#plotly-data-package" title="Permalink to this headline">¶</a></h1>
<div class="section" id="module-plotly.data">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-plotly.data" title="Permalink to this headline">¶</a></h2>
<p>Built-in datasets for demonstration, educational and test purposes.</p>
<dl class="function">
<dt id="plotly.data.carshare">
<code class="sig-prename descclassname">plotly.data.</code><code class="sig-name descname">carshare</code><span class="sig-paren">(</span><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.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p><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-even">Return type</dt>
<dd class="field-even"><p>A <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code> with 249 rows and the following columns</p>
</dd>
</dl>
</dd></dl>
<dl class="function">
<dt id="plotly.data.election">
<code class="sig-prename descclassname">plotly.data.</code><code class="sig-name descname">election</code><span class="sig-paren">(</span><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">Returns</dt>
<dd class="field-odd"><p><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-even">Return type</dt>
<dd class="field-even"><p>A <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code> with 58 rows and the following columns</p>
</dd>
</dl>
</dd></dl>
<dl class="function">
<dt id="plotly.data.election_geojson">
<code class="sig-prename descclassname">plotly.data.</code><code class="sig-name descname">election_geojson</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>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>
is an electoral district numerical ID and whose <code class="docutils literal notranslate"><span class="pre">district</span></code> property is the ID and
district name.</p>
</dd>
</dl>
</dd></dl>
<dl class="function">
<dt id="plotly.data.gapminder">
<code class="sig-prename descclassname">plotly.data.</code><code class="sig-name descname">gapminder</code><span class="sig-paren">(</span><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">Returns</dt>
<dd class="field-odd"><p><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>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>A <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code> with 1704 rows and the following columns</p>
</dd>
</dl>
</dd></dl>
<dl class="function">
<dt id="plotly.data.iris">
<code class="sig-prename descclassname">plotly.data.</code><code class="sig-name descname">iris</code><span class="sig-paren">(</span><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">Returns</dt>
<dd class="field-odd"><p><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-even">Return type</dt>
<dd class="field-even"><p>A <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code> with 150 rows and the following columns</p>
</dd>
</dl>
</dd></dl>
<dl class="function">
<dt id="plotly.data.tips">
<code class="sig-prename descclassname">plotly.data.</code><code class="sig-name descname">tips</code><span class="sig-paren">(</span><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">Returns</dt>
<dd class="field-odd"><p><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-even">Return type</dt>
<dd class="field-even"><p>A <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code> with 244 rows and the following columns</p>
</dd>
</dl>
</dd></dl>
<dl class="function">
<dt id="plotly.data.wind">
<code class="sig-prename descclassname">plotly.data.</code><code class="sig-name descname">wind</code><span class="sig-paren">(</span><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">Returns</dt>
<dd class="field-odd"><p><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-even">Return type</dt>
<dd class="field-even"><p>A <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code> with 128 rows and the following columns</p>
</dd>
</dl>
</dd></dl>
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