joint_plot

joint_plot(data, x, y, *, geom=None, bins=None, binwidth=None, color=None, size=None, alpha=None, color_by=None, show_legend=None, reg_line=None, se=None, marginal=None)

Produce a joint plot that contains bivariate and univariate graphs at the same time.

Parameters:

datadict or Pandas or Polars DataFrame

The data to be displayed.

x, ystr

Names of a variables.

geom{‘point’, ‘tile’, ‘density2d’, ‘density2df’}, default=’point’

The geometric object to use to display the data.

binsint or list of int

Number of bins in both directions, vertical and horizontal. Overridden by binwidth. If only one value given - interpret it as list of two equal values. Applicable simultaneously for ‘tile’ geom and ‘histogram’ marginal.

binwidthfloat or list of float

The width of the bins in both directions, vertical and horizontal. Overrides bins. The default is to use bin widths that cover the entire range of the data. If only one value given - interpret it as list of two equal values. Applicable simultaneously for ‘tile’ geom and ‘histogram’ marginal.

colorstr

Color of the geometry. For more info see Color and Fill.

sizefloat

Size of the geometry.

alphafloat

Transparency level of the geometry. Accept values between 0 and 1.

color_bystr

Name of grouping variable.

show_legendbool, default=True

False - do not show legend for the main layer.

reg_linebool

True - show the line of linear regression.

sebool, default=True

Display confidence interval around regression line.

marginalstr

Description of marginal layers packed to string value. Different marginals are separated by the ‘,’ char. Parameters of a marginal are separated by the ‘:’ char. First parameter of a marginal is a geometry name. Possible values: ‘dens’/’density’, ‘hist’/’histogram’, ‘box’/’boxplot’. Second parameter is a string specifying which sides of the plot the marginal layer will appear on. Possible values: ‘t’ (top), ‘b’ (bottom), ‘l’ (left), ‘r’ (right). Third parameter (optional) is size of marginal. To suppress marginals use marginal=’none’. Examples: “hist:tr:0.3”, “dens:tr,hist:bl”, “box:tr:.05, hist:bl, dens:bl”.

Returns:

PlotSpec

Plot object specification.

Notes

To hide axis tooltips, set ‘blank’ or the result of element_blank() to the axis_tooltip, axis_tooltip_x or axis_tooltip_y parameter of the theme().

Examples

import numpy as np
from lets_plot import *
from lets_plot.bistro.joint import *
LetsPlot.setup_html()
n = 100
np.random.seed(42)
data = {
    'x': np.random.normal(size=n),
    'y': np.random.normal(size=n)
}
joint_plot(data, 'x', 'y')

import numpy as np
from lets_plot import *
from lets_plot.bistro.joint import *
LetsPlot.setup_html()
n = 500
np.random.seed(42)
data = {
    'x': np.random.normal(size=n),
    'y': np.random.normal(size=n)
}
joint_plot(data, 'x', 'y', geom='tile', \
           binwidth=[.5, .5], color="black", \
           marginal="hist:tr,box:bl") + \
    theme_minimal()

import numpy as np
from lets_plot import *
from lets_plot.bistro.joint import *
LetsPlot.setup_html()
n = 500
np.random.seed(42)
data = {
    'x': np.concatenate((np.random.normal(loc=-1, size=n), np.random.normal(loc=2, size=n))),
    'y': np.concatenate((np.random.normal(loc=-.5, size=n), np.random.normal(loc=1.5, size=n))),
    'g': ["A"] * n + ["B"] * n
}
joint_plot(data, 'x', 'y', geom='density2df', color_by='g', alpha=.75)