Boxplot Demo

Example boxplot code

import numpy as np
import matplotlib.pyplot as plt

# Fixing random state for reproducibility
np.random.seed(19680801)

# fake up some data
spread = np.random.rand(50) * 100
center = np.ones(25) * 50
flier_high = np.random.rand(10) * 100 + 100
flier_low = np.random.rand(10) * -100
data = np.concatenate((spread, center, flier_high, flier_low))

fig1, ax1 = plt.subplots()
ax1.set_title('Basic Plot')
ax1.boxplot(data)

Out:

{'whiskers': [<matplotlib.lines.Line2D object at 0x7f155a2c4310>, <matplotlib.lines.Line2D object at 0x7f155a2c4c70>], 'caps': [<matplotlib.lines.Line2D object at 0x7f155a2c4df0>, <matplotlib.lines.Line2D object at 0x7f155a34f760>], 'boxes': [<matplotlib.lines.Line2D object at 0x7f155a2c40d0>], 'medians': [<matplotlib.lines.Line2D object at 0x7f155a34ffa0>], 'fliers': [<matplotlib.lines.Line2D object at 0x7f155a34ff40>], 'means': []}

fig2, ax2 = plt.subplots()
ax2.set_title('Notched boxes')
ax2.boxplot(data, notch=True)

Out:

{'whiskers': [<matplotlib.lines.Line2D object at 0x7f152b114580>, <matplotlib.lines.Line2D object at 0x7f152b114550>], 'caps': [<matplotlib.lines.Line2D object at 0x7f152b114c40>, <matplotlib.lines.Line2D object at 0x7f152b114160>], 'boxes': [<matplotlib.lines.Line2D object at 0x7f15482f5610>], 'medians': [<matplotlib.lines.Line2D object at 0x7f155ef16b20>], 'fliers': [<matplotlib.lines.Line2D object at 0x7f155a2aac10>], 'means': []}

green_diamond = dict(markerfacecolor='g', marker='D')
fig3, ax3 = plt.subplots()
ax3.set_title('Changed Outlier Symbols')
ax3.boxplot(data, flierprops=green_diamond)

Out:

{'whiskers': [<matplotlib.lines.Line2D object at 0x7f155a1a8eb0>, <matplotlib.lines.Line2D object at 0x7f155a1b7250>], 'caps': [<matplotlib.lines.Line2D object at 0x7f155a1b75b0>, <matplotlib.lines.Line2D object at 0x7f155a1b7910>], 'boxes': [<matplotlib.lines.Line2D object at 0x7f155a1a8b50>], 'medians': [<matplotlib.lines.Line2D object at 0x7f155a1b7c40>], 'fliers': [<matplotlib.lines.Line2D object at 0x7f155a1b7f40>], 'means': []}

fig4, ax4 = plt.subplots()
ax4.set_title('Hide Outlier Points')
ax4.boxplot(data, showfliers=False)

Out:

{'whiskers': [<matplotlib.lines.Line2D object at 0x7f155a34edf0>, <matplotlib.lines.Line2D object at 0x7f155a33ed00>], 'caps': [<matplotlib.lines.Line2D object at 0x7f155a33eb80>, <matplotlib.lines.Line2D object at 0x7f155a33ed60>], 'boxes': [<matplotlib.lines.Line2D object at 0x7f155a34ea90>], 'medians': [<matplotlib.lines.Line2D object at 0x7f155a33e520>], 'fliers': [], 'means': []}

red_square = dict(markerfacecolor='r', marker='s')
fig5, ax5 = plt.subplots()
ax5.set_title('Horizontal Boxes')
ax5.boxplot(data, vert=False, flierprops=red_square)

Out:

{'whiskers': [<matplotlib.lines.Line2D object at 0x7f155a194d60>, <matplotlib.lines.Line2D object at 0x7f155a1a0100>], 'caps': [<matplotlib.lines.Line2D object at 0x7f155a1a0460>, <matplotlib.lines.Line2D object at 0x7f155a1a07c0>], 'boxes': [<matplotlib.lines.Line2D object at 0x7f155a194a00>], 'medians': [<matplotlib.lines.Line2D object at 0x7f155a1a0af0>], 'fliers': [<matplotlib.lines.Line2D object at 0x7f155a1a0df0>], 'means': []}

fig6, ax6 = plt.subplots()
ax6.set_title('Shorter Whisker Length')
ax6.boxplot(data, flierprops=red_square, vert=False, whis=0.75)

Out:

{'whiskers': [<matplotlib.lines.Line2D object at 0x7f155a211d90>, <matplotlib.lines.Line2D object at 0x7f155a215130>], 'caps': [<matplotlib.lines.Line2D object at 0x7f155a215490>, <matplotlib.lines.Line2D object at 0x7f155a2157f0>], 'boxes': [<matplotlib.lines.Line2D object at 0x7f155a211a30>], 'medians': [<matplotlib.lines.Line2D object at 0x7f155a215b20>], 'fliers': [<matplotlib.lines.Line2D object at 0x7f155a215e20>], 'means': []}

Fake up some more data

spread = np.random.rand(50) * 100
center = np.ones(25) * 40
flier_high = np.random.rand(10) * 100 + 100
flier_low = np.random.rand(10) * -100
d2 = np.concatenate((spread, center, flier_high, flier_low))
data.shape = (-1, 1)
d2.shape = (-1, 1)

Making a 2-D array only works if all the columns are the same length. If they are not, then use a list instead. This is actually more efficient because boxplot converts a 2-D array into a list of vectors internally anyway.

data = [data, d2, d2[::2, 0]]
fig7, ax7 = plt.subplots()
ax7.set_title('Multiple Samples with Different sizes')
ax7.boxplot(data)

plt.show()

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References

The use of the following functions, methods, classes and modules is shown in this example:

import matplotlib
matplotlib.axes.Axes.boxplot
matplotlib.pyplot.boxplot

Out:

<function boxplot at 0x7f154d0c7ca0>