How do I get the diagonal of sns.pairplot?

Question

OK I am probably being thick, but how do I get just the graphs in the diagonal (top left to bottom right) in a nice row or 2x2 grid of:

import seaborn as sns; sns.set(style="ticks", color_codes=True)
iris = sns.load_dataset("iris")
g = sns.pairplot(iris, hue="species", palette="husl")

TO CLARIFY: I just want these graphs I do not care whether pairplot or something else is used.

ImportanceOfBeingErnest · Accepted Answer · 2019-12-07T12:00:01.937

6

Doing this the seaborn-way would make use of a FacetGrid. For this we would need to convert the wide-form input to a long-form dataframe, such that every observation is a single row. This is done via pandas.melt.

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

iris = sns.load_dataset("iris")
df = pd.melt(iris, iris.columns[-1], iris.columns[:-1])

g = sns.FacetGrid(df, col="variable", hue="species", col_wrap=2)
g.map(sns.kdeplot, "value", shade=True)

plt.show()

edited Dec 07 '19 at 12:00

answered Dec 06 '19 at 15:56

ImportanceOfBeingErnest

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Your plot will look a lot better if you add sharex=False, sharey=False to the FacetGrid command. – KRKirov Dec 06 '19 at 17:48
@KRKirov Thanks, but sharing the axes makes the plots comparable quantitatively. So this is shown like it is on purpose. – ImportanceOfBeingErnest Dec 06 '19 at 17:51
Fair enough if this is the purpose. There is an awful a lot of unused space in the plot though. – KRKirov Dec 06 '19 at 17:52
You don't make plots because you want to win Art competitions, but rather to easily identify relations in data. – ImportanceOfBeingErnest Dec 06 '19 at 17:53
Let's not get into philosophical debates about plots and how they should be constructed. – KRKirov Dec 06 '19 at 17:56
I didn't start this. – ImportanceOfBeingErnest Dec 06 '19 at 18:04
Thanks exactly what I needed. Could you expain what df = pd.melt(iris, iris.columns[-1], iris.columns[:-1]) does? – schoon Dec 07 '19 at 09:00
It basically converts wide-form frame to long-form, because FacetGrid only works with long form data. It's like unpivoting, but keeping one or more columns (in this case the "species"). – ImportanceOfBeingErnest Dec 07 '19 at 12:01
I was just using this answer and noticed the legend was missing. Add this line at the bottom to show the legend. **`g.add_legend()`** – Sashi Jul 18 '23 at 07:06

Soumendra Bagh · Answer 2 · 2019-12-06T13:10:04.217

Why do you even want to do that. The diagonal of the pairplot gives you the distplot of that feature. It will be more effective if you can plot the idividual distplots as subplot or mux them Ex:

import numpy as np
import pandas as pd
from sklearn.datasets import load_iris
import seaborn as sns

iris = load_iris()
iris = pd.DataFrame(data=np.c_[iris['data'], iris['target']],
                    columns=iris['feature_names'] + ['target'])

# Sort the dataframe by target
target_0 = iris.loc[iris['target'] == 0]
target_1 = iris.loc[iris['target'] == 1]
target_2 = iris.loc[iris['target'] == 2]

sns.distplot(target_0[['sepal length (cm)']], hist=False, rug=True)
sns.distplot(target_1[['sepal length (cm)']], hist=False, rug=True)
sns.distplot(target_2[['sepal length (cm)']], hist=False, rug=True)

sns.plt.show()

The output will be somewhat like this: Distplot [1]

Read more here : python: distplot with multiple distributions

I wanted a grid. But this is useful too. Thanks +1. – schoon Dec 07 '19 at 09:00 — schoon, Dec 07 '19 at 09:00
Glad I could help out. – Soumendra Bagh Dec 07 '19 at 14:40 — Soumendra Bagh, Dec 07 '19 at 14:40

score 0 · Answer 3 · answered Dec 06 '19 at 12:00

0

import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="ticks", color_codes=True)
iris = sns.load_dataset("iris")

def hide_current_axis(*args, **kwds):
    plt.gca().set_visible(False)

g = sns.pairplot(iris, hue="species", palette="husl")
g.map_upper(hide_current_axis)
g.map_lower(hide_current_axis)

Output:

answered Dec 06 '19 at 12:00

Harish Vutukuri

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Thanks but is there a way to output it in a row or 2x2 grid? – schoon Dec 06 '19 at 12:03

KRKirov · Answer 4 · 2019-12-06T17:50:59.400

0

plt.subplots(2, 2)
for i, col in enumerate(iris.columns[:4]):
    plt.subplot(2, 2, i+1)
    sns.kdeplot(iris.loc[iris['species'] == 'setosa', col], shade=True, label='setosa')
    sns.kdeplot(iris.loc[iris['species'] == 'versicolor', col], shade=True, label='versicolor')
    sns.kdeplot(iris.loc[iris['species'] == 'virginica', col], shade=True, label='virginica')
    plt.xlabel('cm')
    plt.title(col)
    if i == 1:
        plt.legend(loc='upper right')
    else:
        plt.legend().remove()

plt.subplot_tool() # Opens a widget which allows adjusting plot aesthetics

edited Dec 06 '19 at 17:50

answered Dec 06 '19 at 12:59

KRKirov

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Ah I did not see this answer before accepting the other one. Looks good although a little more complex. Thanks. – schoon Dec 07 '19 at 09:02

Leonardo Queiroz · Answer 5 · 2022-10-15T03:33:57.227

-2

import seaborn as sns
import matplotlib.pyplot as plt
iris = sns.load_dataset("iris")

sns.pairplot(iris, hue="species", corner=True)

edited Oct 15 '22 at 03:33

answered Oct 15 '22 at 03:28

Leonardo Queiroz

7
2

Your answer keeps the lower triangle plots there, but this isn't exactly what OP wanted. The question suggested to keep the diagonal plots only. – Nikita Shabankin Oct 17 '22 at 18:24

How do I get the diagonal of sns.pairplot?

5 Answers5