Note

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# Example with the plotly graphing library

Sphinx-Gallery supports examples made with the plotly library. Sphinx-Gallery is able to capture the `_repr_html_` of plotly figure objects (see Controlling what output is captured). To display the figure, the last line in your code block should therefore be the plotly figure object.

In order to use plotly, the `conf.py` of the project should include the following lines to select the appropriate plotly renderer:

    import plotly.io as pio
    pio.renderers.default = 'sphinx_gallery'

Optional: the `sphinx_gallery` renderer of plotly will not generate png thumbnails. For png thumbnails, you can use instead the `sphinx_gallery_png` renderer, and add `plotly.io._sg_scraper.plotly_sg_scraper` to the list of Image scrapers. The scraper requires you to install the orca package.

This tutorial gives a few examples of plotly figures, starting with its high-level API plotly express.

    import plotly.express as px
    import numpy as np

    df = px.data.tips()
    fig = px.bar(df, x='sex', y='total_bill', facet_col='day', color='smoker', barmode='group',
                 template='presentation+plotly'
                 )
    fig.update_layout(height=400)
    fig

In addition to the classical scatter or bar charts, plotly provides a large variety of traces, such as the sunburst hierarchical trace of the following example. plotly is an interactive library: click on one of the continents for a more detailed view of the drill-down.

    df = px.data.gapminder().query("year == 2007")
    fig = px.sunburst(df, path=['continent', 'country'], values='pop',
                      color='lifeExp', hover_data=['iso_alpha'],
                      color_continuous_scale='RdBu',
                      color_continuous_midpoint=np.average(df['lifeExp'], weights=df['pop']))
    fig.update_layout(title_text='Life expectancy of countries and continents')
    fig

While plotly express is often the high-level entry point of the plotly library, complex figures mixing different types of traces can be made with the low-level `graph_objects` imperative API.

    from plotly.subplots import make_subplots
    import plotly.graph_objects as go
    fig = make_subplots(rows=1, cols=2, specs=[[{}, {'type':'domain'}]])
    fig.add_trace(go.Bar(x=[2018, 2019, 2020], y=[3, 2, 5], showlegend=False), 1, 1)
    fig.add_trace(go.Pie(labels=['A', 'B', 'C'], values=[1, 3, 6]), 1, 2)
    fig.update_layout(height=400, template='presentation', yaxis_title_text='revenue')
    fig

    # sphinx_gallery_thumbnail_path = '_static/plotly_logo.png'

Estimated memory usage: 21 MB

Gallery generated by Sphinx-Gallery