Joint Plot#

import altair_express as alx
from vega_datasets import data

alx.jointplot(data=data.cars(),x='Miles_per_Gallon',y='Horsepower')

The jointplot() function is useful for understanding the distribution and relationship between two variables in a dataset. Using a scatterplot plot with marginal histogram plots, Jointplots assist in understanding how variables might interact.

Parameters#

datapandas dataframe

The data to visualize as a pandas dataframe.

xstring

The column name of the categorical series used for the x axis.

ystring

The column name of the categorical series used for the y axis.

colorstring

A valid CSS color to make the chart or a column name in the dataframe to color the bars by.

widthint

The width of the chart in pixels.

heightint

The height of the chart in pixels.

effectsEffect Objects

The effects of interactions to be applied to the chart.

Examples#

Interactive Brush#

import altair_express as alx
from vega_datasets import data

alx.highlight_brush() + alx.jointplot(data=data.cars(),x='Miles_per_Gallon',y='Horsepower')