Joint plot

import pandas as pd

from lets_plot.bistro import *
from lets_plot import *

LetsPlot.setup_html()

df = pd.read_csv("https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/iris.csv")
print(df.shape)
df.head()

(150, 5)

	sepal_length	sepal_width	petal_length	petal_width	species
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
4	5.0	3.6	1.4	0.2	setosa

1. Default Presentation of Joint Plot

In the simplest case, assign x and y to create a scatterplot (using geom_point()) with marginal histograms (using geom_histogram()).

joint_plot(df, "petal_length", "petal_width")

2. Change Geom Types

In addition to the points, there are a few other types of geoms: tile, density2d(f), pointdensity.

joint_plot(df, "petal_length", "petal_width", geom='tile')

joint_plot(df, "petal_length", "petal_width", color_by="species", geom='density2d')

joint_plot(df, "petal_length", "petal_width", geom='pointdensity')

3. Change Geom Parameters

Use additional parameters for better customization: color, size, alpha, etc.

joint_plot(df, "petal_length", "petal_width", color="#756bb1", size=8, alpha=.5, se=False)

4. Marginal Layers Customization

marginal parameter is a shortcut for the ggmarginal() layer.

joint_plot(df, "petal_length", "petal_width", color="black", marginal="box:lb:.03,hist:t:.4,hist:r") + \
    ggmarginal("tr", layer=geom_area(stat='density', color="magenta", fill="magenta", alpha=.1)) + \
    theme(axis_line_x='blank', axis_line_y='blank')

5. Grouping

The color_by parameter sets the mapping to the fill and color aesthetics.

joint_plot(df, "petal_length", "petal_width", color_by="species", marginal="hist:tr")

6. Additional Layer

Add any other layer that supports x and y aesthetics (e.g. points layer with the geom_point() function).

joint_plot(df, "petal_length", "petal_width", geom='density2df', \
           color="#993404", alpha=1/3, reg_line=False) + \
    geom_point(size=5, shape=21, color="#993404", fill="#ffffd4") + \
    scale_fill_gradient(low="#d95f0e", high="#fff7bc")