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Marginal plots

Overview

Marginal distribution plots are small subplots above or to the right of a main plot, which show the distribution of data along only one dimension. Marginal distribution plot capabilities are built into various Plotly Express functions such as scatter and histogram. Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.

Scatter Plot Marginals

The marginal_x and marginal_y arguments accept one of "histogram", "rug", "box", or "violin" (see also how to create histograms, box plots and violin plots as the main figure).

Marginal plots are linked to the main plot: try zooming or panning on the main plot.

Marginal plots also support hover, including per-point hover as with the rug-plot on the right: try hovering over the points on the right marginal plot.

import plotly.express as px
df = px.data.iris()
fig = px.scatter(df, x="sepal_length", y="sepal_width", marginal_x="histogram", marginal_y="rug")
fig.show()

import plotly.express as px
df = px.data.iris()
fig = px.density_heatmap(df, x="sepal_length", y="sepal_width", marginal_x="box", marginal_y="violin")
fig.show()

Marginal Plots and Color

Marginal plots respect the color argument as well, and are linked to the respective legend elements. Try clicking on the legend items.

import plotly.express as px
df = px.data.iris()
fig = px.scatter(df, x="sepal_length", y="sepal_width", color="species", 
                 marginal_x="box", marginal_y="violin",
                  title="Click on the legend items!")
fig.show()

Marginal Plots on Histograms

Histograms are often used to show the distribution of a variable, and they also support marginal plots in Plotly Express, with the marginal argument:

import plotly.express as px
df = px.data.iris()
fig = px.histogram(df, x="sepal_length", color="species", marginal="box")
fig.show()

Try hovering over the rug plot points to identify individual country values in the histogram below:

import plotly.express as px
df = px.data.gapminder().query("year == 2007")
fig = px.histogram(df, x="lifeExp", color="continent", marginal="rug", hover_name="country",
                  title="Hover over the rug plot!")
fig.show()

Marginal Plots and Facets

Marginal plots can be used in conjunction with Plotly Express facets so long as they go along different directions: 

import plotly.express as px
df = px.data.tips()
fig = px.scatter(df, x="total_bill", y="tip", color="sex", facet_col="day",
                  marginal_x="box")
fig.show()

import plotly.express as px
df = px.data.tips()
fig = px.scatter(df, x="total_bill", y="tip", color="sex", facet_row="time",
                  marginal_y="box")
fig.show()

import plotly.express as px
df = px.data.tips()
fig = px.histogram(df, x="total_bill", y="tip", color="sex", facet_col="day",
                  marginal="box")
fig.show()
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