matplotlib.github.com/2.2.3/gallery/statistics/bxp.py at main · matplotlib/matplotlib.github.com · GitHub

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"""

=======================

Boxplot drawer function

=======================

This example demonstrates how to pass pre-computed box plot

statistics to the box plot drawer. The first figure demonstrates

how to remove and add individual components (note that the

mean is the only value not shown by default). The second

figure demonstrates how the styles of the artists can

be customized.

A good general reference on boxplots and their history can be found

here: http://vita.had.co.nz/papers/boxplots.pdf

"""

import numpy as np

import matplotlib.pyplot as plt

import matplotlib.cbook as cbook

# fake data

np.random.seed(19680801)

data = np.random.lognormal(size=(37, 4), mean=1.5, sigma=1.75)

labels = list('ABCD')

# compute the boxplot stats

stats = cbook.boxplot_stats(data, labels=labels, bootstrap=10000)

###############################################################################

# After we've computed the stats, we can go through and change anything.

# Just to prove it, I'll set the median of each set to the median of all

# the data, and double the means

for n in range(len(stats)):

stats[n]['med'] = np.median(data)

stats[n]['mean'] *= 2

print(list(stats[0]))

fs = 10 # fontsize

###############################################################################

# Demonstrate how to toggle the display of different elements:

fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(6, 6), sharey=True)

axes[0, 0].bxp(stats)

axes[0, 0].set_title('Default', fontsize=fs)

axes[0, 1].bxp(stats, showmeans=True)

axes[0, 1].set_title('showmeans=True', fontsize=fs)

axes[0, 2].bxp(stats, showmeans=True, meanline=True)

axes[0, 2].set_title('showmeans=True,\nmeanline=True', fontsize=fs)

axes[1, 0].bxp(stats, showbox=False, showcaps=False)

tufte_title = 'Tufte Style\n(showbox=False,\nshowcaps=False)'

axes[1, 0].set_title(tufte_title, fontsize=fs)

axes[1, 1].bxp(stats, shownotches=True)

axes[1, 1].set_title('notch=True', fontsize=fs)

axes[1, 2].bxp(stats, showfliers=False)

axes[1, 2].set_title('showfliers=False', fontsize=fs)

for ax in axes.flatten():

ax.set_yscale('log')

ax.set_yticklabels([])

fig.subplots_adjust(hspace=0.4)

plt.show()

###############################################################################

# Demonstrate how to customize the display different elements:

boxprops = dict(linestyle='--', linewidth=3, color='darkgoldenrod')

flierprops = dict(marker='o', markerfacecolor='green', markersize=12,

linestyle='none')

medianprops = dict(linestyle='-.', linewidth=2.5, color='firebrick')

meanpointprops = dict(marker='D', markeredgecolor='black',

markerfacecolor='firebrick')

meanlineprops = dict(linestyle='--', linewidth=2.5, color='purple')

fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(6, 6), sharey=True)

axes[0, 0].bxp(stats, boxprops=boxprops)

axes[0, 0].set_title('Custom boxprops', fontsize=fs)

axes[0, 1].bxp(stats, flierprops=flierprops, medianprops=medianprops)

axes[0, 1].set_title('Custom medianprops\nand flierprops', fontsize=fs)

axes[1, 0].bxp(stats, meanprops=meanpointprops, meanline=False,

showmeans=True)

axes[1, 0].set_title('Custom mean\nas point', fontsize=fs)

axes[1, 1].bxp(stats, meanprops=meanlineprops, meanline=True,

showmeans=True)

axes[1, 1].set_title('Custom mean\nas line', fontsize=fs)

for ax in axes.flatten():

ax.set_yscale('log')

ax.set_yticklabels([])

fig.suptitle("I never said they'd be pretty")

fig.subplots_adjust(hspace=0.4)

plt.show()

matplotlib.github.com/2.2.3/gallery/statistics/bxp.py at main · matplotlib/matplotlib.github.com · GitHub

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