python - How to align split violin plots with seaborn? - Stack Overflow

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I am trying to plot split violin plots with Seaborn, i.e. a pair of KDE plots stacked against each other, typically to see the difference between distributions.

My use case is very similar to the docs except I would like to superimpose custom box plots on top (as in this tutorial) However, I am having a strange alignment issue with the violin plots with respect to the X axis and I don't understand what I am doing differently from the docs...

Here's code for a MRE with only split violins:

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
import seaborn as sns

sns.set_theme()

data1 = np.random.normal(0, 1, 1000)
data2 = np.random.normal(1, 2, 1000)

data = pd.concat(
    [
        pd.DataFrame({"column": "1", "data1": data1, "data2": data2}),
        pd.DataFrame({"column": "2", "data3": data2, "data4": data1}),
    ],
    axis="rows",
)


def mkplot():
    fig, violin_ax = plt.subplots()
    sns.violinplot(
        data=data.melt(id_vars="column"),
        y="value",
        split=True,
        hue="variable",
        x="column",
        ax=violin_ax,
        palette="Paired",
        bw_method="silverman",
        inner=None,
    )
    plt.show()

mkplot()

This produces split violins whose middle is not aligned with the X axis label: mis-aligned violins

(this is also true when "column" is of numeric type rather than str)

It seems that box plots are also mis-aligned, but not with the same magnitude; you can use the function below with the same data

def mkplot2():
    fig, violin_ax = plt.subplots()
    sns.violinplot(
        data=data.melt(id_vars="column"),
        y="value",
        split=True,
        hue="variable",
        x="column",
        ax=violin_ax,
        palette="Paired",
        bw_method="silverman",
        inner=None,
    )
    sns.boxplot(
        data=data.melt(id_vars="column"),
        y="value",
        hue="variable",
        x="column",
        ax=violin_ax,
        palette="Paired",
        width=0.3,
        flierprops={"marker": "o", "markersize": 3},
        legend=False,
        dodge=True,
    )
    plt.show()

mkplot2()

mis-aligned violins+boxes

How can I solve this ?

I am trying to plot split violin plots with Seaborn, i.e. a pair of KDE plots stacked against each other, typically to see the difference between distributions.

My use case is very similar to the docs except I would like to superimpose custom box plots on top (as in this tutorial) However, I am having a strange alignment issue with the violin plots with respect to the X axis and I don't understand what I am doing differently from the docs...

Here's code for a MRE with only split violins:

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
import seaborn as sns

sns.set_theme()

data1 = np.random.normal(0, 1, 1000)
data2 = np.random.normal(1, 2, 1000)

data = pd.concat(
    [
        pd.DataFrame({"column": "1", "data1": data1, "data2": data2}),
        pd.DataFrame({"column": "2", "data3": data2, "data4": data1}),
    ],
    axis="rows",
)


def mkplot():
    fig, violin_ax = plt.subplots()
    sns.violinplot(
        data=data.melt(id_vars="column"),
        y="value",
        split=True,
        hue="variable",
        x="column",
        ax=violin_ax,
        palette="Paired",
        bw_method="silverman",
        inner=None,
    )
    plt.show()

mkplot()

This produces split violins whose middle is not aligned with the X axis label: mis-aligned violins

(this is also true when "column" is of numeric type rather than str)

It seems that box plots are also mis-aligned, but not with the same magnitude; you can use the function below with the same data

def mkplot2():
    fig, violin_ax = plt.subplots()
    sns.violinplot(
        data=data.melt(id_vars="column"),
        y="value",
        split=True,
        hue="variable",
        x="column",
        ax=violin_ax,
        palette="Paired",
        bw_method="silverman",
        inner=None,
    )
    sns.boxplot(
        data=data.melt(id_vars="column"),
        y="value",
        hue="variable",
        x="column",
        ax=violin_ax,
        palette="Paired",
        width=0.3,
        flierprops={"marker": "o", "markersize": 3},
        legend=False,
        dodge=True,
    )
    plt.show()

mkplot2()

mis-aligned violins+boxes

How can I solve this ?

• python
• matplotlib
• seaborn

Share Improve this question Follow asked Jan 21 at 17:24 louisbzklouisbzk 3333 bronze badges

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2 Answers 2

Sorted by: Reset to default 2

The issue is due to the NaNs that you have after melting. This makes 4 groups and thus the violins are shifted to account for those.

You could plot the groups independently:

data_flat = data.melt('column').dropna(subset='value')
violin_ax = plt.subplot()
pal = sns.color_palette('Paired')

for i, (name, g) in enumerate(data_flat.groupby('column')):
    sns.violinplot(
        data=g,
        y='value',
        split=True,
        hue='variable',
        x='column',
        ax=violin_ax,
        palette=pal[2*i:2*i+2],
        bw_method='silverman',
        inner=None,
    )

Output:

If you are fine with the location of the violinplots, you can simply move the xtick labels:

violin_ax.set_xticks([-0.2, 1.2])

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