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Copy file name to clipboardExpand all lines: src/pages/connected-scatter-plot.js
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@@ -16,16 +16,20 @@ import Spacing from "../components/Spacing";
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constchartDescription=
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"<p>A <a href='https://www.data-to-viz.com/graph/connectedscatter.html'>connected scatterplot</a> is a <a href='https://python-graph-gallery.com/line-chart/'>line chart</a> where each data point is shown by a circle or any type of marker. This section explains how to build a connected scatterplot with <code>Python</code>, using both the <code>Matplotlib</code> and the <code>Seaborn</code> libraries.</p>";
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<h2id="Quick">⏱ Quick start</h2>
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<RowclassName="align-items-center">
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<Colmd={6}>
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<p>TODO.🔥</p>
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<p>Building a connected scatterplot with Python and Matplotlib is a breeze thanks to
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the <code>plot()</code> function. The 2 first argumenst are the X and Y values respectively, which
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can be stored in a <code>pandas</code> data frame.</p>
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<p>The <code>linestyle</code> and <code>marker</code> arguments allow to use line and circles to make it look like
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a connected scatterplot. It means everything is very close to a <Linkto="/line-chart">line chart</Link> or a <Linkto="/scatter-plot">scatterplot</Link> that
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are extensively described in the gallery.</p>
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</Col>
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<Colmd={6}>
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<Linkto={"/132-basic-connected-scatterplot"}>
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a line chart, so feel free to visit the related section. Here are a few examples to remind the
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basics and understand how to customize the markers.
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</p>
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<Row>
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<ChartImageContainer
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imgName="132_Matplotlib-connected-scatterplot"
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caption="Basic connected scatterplot with Python and Seaborn."
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