1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
|
"""
=====================================================
The histogram (hist) function with multiple data sets
=====================================================
Plot histogram with multiple sample sets and demonstrate:
* Use of legend with multiple sample sets
* Stacked bars
* Step curve with no fill
* Data sets of different sample sizes
Selecting different bin counts and sizes can significantly affect the
shape of a histogram. The Astropy docs have a great section on how to
select these parameters:
http://docs.astropy.org/en/stable/visualization/histogram.html
.. redirect-from:: /gallery/lines_bars_and_markers/filled_step
"""
# %%
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(19680801)
n_bins = 10
x = np.random.randn(1000, 3)
fig, ((ax0, ax1), (ax2, ax3)) = plt.subplots(nrows=2, ncols=2)
colors = ['red', 'tan', 'lime']
ax0.hist(x, n_bins, density=True, histtype='bar', color=colors, label=colors)
ax0.legend(prop={'size': 10})
ax0.set_title('bars with legend')
ax1.hist(x, n_bins, density=True, histtype='bar', stacked=True)
ax1.set_title('stacked bar')
ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False)
ax2.set_title('stack step (unfilled)')
# Make a multiple-histogram of data-sets with different length.
x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]]
ax3.hist(x_multi, n_bins, histtype='bar')
ax3.set_title('different sample sizes')
fig.tight_layout()
plt.show()
# %%
# -----------------------------------
# Setting properties for each dataset
# -----------------------------------
#
# You can style the histograms individually by passing a list of values to the
# following parameters:
#
# * edgecolor
# * facecolor
# * hatch
# * linewidth
# * linestyle
#
#
# edgecolor
# .........
fig, ax = plt.subplots()
edgecolors = ['green', 'red', 'blue']
ax.hist(x, n_bins, fill=False, histtype="step", stacked=True,
edgecolor=edgecolors, label=edgecolors)
ax.legend()
ax.set_title('Stacked Steps with Edgecolors')
plt.show()
# %%
# facecolor
# .........
fig, ax = plt.subplots()
facecolors = ['green', 'red', 'blue']
ax.hist(x, n_bins, histtype="barstacked", facecolor=facecolors, label=facecolors)
ax.legend()
ax.set_title("Bars with different Facecolors")
plt.show()
# %%
# hatch
# .....
fig, ax = plt.subplots()
hatches = [".", "o", "x"]
ax.hist(x, n_bins, histtype="barstacked", hatch=hatches, label=hatches)
ax.legend()
ax.set_title("Hatches on Stacked Bars")
plt.show()
# %%
# linewidth
# .........
fig, ax = plt.subplots()
linewidths = [1, 2, 3]
edgecolors = ["green", "red", "blue"]
ax.hist(x, n_bins, fill=False, histtype="bar", linewidth=linewidths,
edgecolor=edgecolors, label=linewidths)
ax.legend()
ax.set_title("Bars with Linewidths")
plt.show()
# %%
# linestyle
# .........
fig, ax = plt.subplots()
linestyles = ['-', ':', '--']
ax.hist(x, n_bins, fill=False, histtype='bar', linestyle=linestyles,
edgecolor=edgecolors, label=linestyles)
ax.legend()
ax.set_title('Bars with Linestyles')
plt.show()
# %%
#
# .. tags:: plot-type: histogram, domain: statistics, purpose: reference
#
# .. admonition:: References
#
# The use of the following functions, methods, classes and modules is shown
# in this example:
#
# - `matplotlib.axes.Axes.hist` / `matplotlib.pyplot.hist`
|
