CODEWITHSUNDEEP
pythonmatplotlibseaborn
ali bakhtiari
ali bakhtiari

Reputation: 1097

hatching seaborn countplot by hue

I am trying to manipulate hatch of a countplot by hue. Here is the plot code and the corresponding plot I drew:

ax = sns.countplot(
    data=data, y='M_pattern', hue='HHFAMINC',
    palette=color_palette, lw=0.5, ec='black',
    )
plt.yticks(rotation=45, ha='right')
legend_labels, _ = ax.get_legend_handles_labels()

hatches = ['-', '+', 'x', '\\']

# Loop over the bars
for i,thisbar in enumerate(bar.patches):
    # Set a different hatch for each bar
    thisbar.set_hatch(hatches[i])

    
plt.legend(
    legend_labels, [
        'Less than 10,000$ to 50,000$',
        '50,000$ to 100,000$',
        '100,000 to 150,000$',
        'More than 150,000'
        ]
    , title='Income categories'
    )

plt.ylabel('Mandatory trip pattern')
plt.show()

enter image description here

Is there an straightforward way to hatch each income category separately?

Upvotes: 2

Views: 529

Answers (1)

JohanC
JohanC

Reputation: 80509

ax.containers contains a list of each group of bars. To access individual bars, you can first loop through the containers and then through each of the bars. Instead of working with enumerate, it is highly recommended to use zip to simultaneously loop through two lists.

To rename legend entries, a replace onto the elements of the hue columns makes sure the correspondence between value and long name keeps intact after the dataset would be updated.

Here is an example using seaborn's 'tips' dataset. Here 3*hatch_pattern makes the hatching 3 times as dense.

import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np

data = sns.load_dataset('tips')
ax = sns.countplot(
    data=data.replace({'day': {'Thur': 'Thursday', 'Fri': 'Friday', 'Sat': 'Saturday', 'Sun': 'Sunday'}}),
    y='time', hue='day',
    palette='Set2', lw=0.5, ec='black')
plt.yticks(rotation=45, ha='right')

hatches = ['-', '+', 'x', '\\']

for hatch_pattern, these_bars in zip(hatches, ax.containers):
    for this_bar in these_bars:
        this_bar.set_hatch(3 * hatch_pattern)
ax.legend(loc='upper right', title='Days')

plt.show()

seaborn countplot with hatching

Upvotes: 3

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