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How to set seaborn jointplot axis to log scale
Asked Answered
Solved pythonpandasmatplotlibseabornjointplot
K

1

8

How to set axis to logarithmic scale in a seaborn jointplot? I can't find any log arguments in seaborn.jointplot

Notebook

import seaborn as sns
import pandas as pd

df = pd.read_csv("https://storage.googleapis.com/mledu-datasets/california_housing_train.csv", sep=",")

g = sns.jointplot(x="total_bedrooms",
              y="median_house_value",
              data = df,
              kind="reg",
              logx=True
              )

enter image description here

  • 300 rows of sample data of the relevant columns, incase the data link dies
median_house_value,total_bedrooms
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Kee answered 27/6, 2018 at 8:52 Comment(0)
P
18

After you create the plot, you can set the axes to be log scale, using matplotlib's ax.set_xscale('log') and ax.set_yscale('log').

In this case, we need to get the axis from the JointGrid created by jointplot. If you catch the JointGrid returned as g, then the joint axis is g.ax_joint.

For example:

g = sns.jointplot(x="predictions",
              y="targets",
              data = calibration_data,
              kind="reg",
              logx=True,
              )

g.ax_joint.set_xscale('log')
g.ax_joint.set_yscale('log')
Paunch answered 27/6, 2018 at 11:0 Comment(1)
That works! for other users, you might want to change your axes limits using g.ax_joint.set_xlim([xmin,xmax]) – Kee

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