.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "gallery/statistics/customized_violin.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_statistics_customized_violin.py: ========================= Violin plot customization ========================= This example demonstrates how to fully customize violin plots. The first plot shows the default style by providing only the data. The second plot first limits what matplotlib draws with additional kwargs. Then a simplified representation of a box plot is drawn on top. Lastly, the styles of the artists of the violins are modified. For more information on violin plots, the scikit-learn docs have a great section: https://scikit-learn.org/stable/modules/density.html .. GENERATED FROM PYTHON SOURCE LINES 16-77 .. image:: /gallery/statistics/images/sphx_glr_customized_violin_001.png :alt: Default violin plot, Customized violin plot :class: sphx-glr-single-img .. code-block:: default import matplotlib.pyplot as plt import numpy as np def adjacent_values(vals, q1, q3): upper_adjacent_value = q3 + (q3 - q1) * 1.5 upper_adjacent_value = np.clip(upper_adjacent_value, q3, vals[-1]) lower_adjacent_value = q1 - (q3 - q1) * 1.5 lower_adjacent_value = np.clip(lower_adjacent_value, vals[0], q1) return lower_adjacent_value, upper_adjacent_value def set_axis_style(ax, labels): ax.get_xaxis().set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, len(labels) + 1)) ax.set_xticklabels(labels) ax.set_xlim(0.25, len(labels) + 0.75) ax.set_xlabel('Sample name') # create test data np.random.seed(19680801) data = [sorted(np.random.normal(0, std, 100)) for std in range(1, 5)] fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(9, 4), sharey=True) ax1.set_title('Default violin plot') ax1.set_ylabel('Observed values') ax1.violinplot(data) ax2.set_title('Customized violin plot') parts = ax2.violinplot( data, showmeans=False, showmedians=False, showextrema=False) for pc in parts['bodies']: pc.set_facecolor('#D43F3A') pc.set_edgecolor('black') pc.set_alpha(1) quartile1, medians, quartile3 = np.percentile(data, [25, 50, 75], axis=1) whiskers = np.array([ adjacent_values(sorted_array, q1, q3) for sorted_array, q1, q3 in zip(data, quartile1, quartile3)]) whiskers_min, whiskers_max = whiskers[:, 0], whiskers[:, 1] inds = np.arange(1, len(medians) + 1) ax2.scatter(inds, medians, marker='o', color='white', s=30, zorder=3) ax2.vlines(inds, quartile1, quartile3, color='k', linestyle='-', lw=5) ax2.vlines(inds, whiskers_min, whiskers_max, color='k', linestyle='-', lw=1) # set style for the axes labels = ['A', 'B', 'C', 'D'] for ax in [ax1, ax2]: set_axis_style(ax, labels) plt.subplots_adjust(bottom=0.15, wspace=0.05) plt.show() .. _sphx_glr_download_gallery_statistics_customized_violin.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: customized_violin.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: customized_violin.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature Keywords: matplotlib code example, codex, python plot, pyplot `Gallery generated by Sphinx-Gallery `_