条形标签演示#

此示例说明如何使用bar_label辅助函数创建条形图标签。

import matplotlib.pyplot as plt
import numpy as np

定义数据

N = 5
menMeans = (20, 35, 30, 35, -27)
womenMeans = (25, 32, 34, 20, -25)
menStd = (2, 3, 4, 1, 2)
womenStd = (3, 5, 2, 3, 3)
ind = np.arange(N)    # the x locations for the groups
width = 0.35       # the width of the bars: can also be len(x) sequence

带有误差线的堆积条形图

fig, ax = plt.subplots()

p1 = ax.bar(ind, menMeans, width, yerr=menStd, label='Men')
p2 = ax.bar(ind, womenMeans, width,
            bottom=menMeans, yerr=womenStd, label='Women')

ax.axhline(0, color='grey', linewidth=0.8)
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(ind, labels=['G1', 'G2', 'G3', 'G4', 'G5'])
ax.legend()

# Label with label_type 'center' instead of the default 'edge'
ax.bar_label(p1, label_type='center')
ax.bar_label(p2, label_type='center')
ax.bar_label(p2)

plt.show()

水平条形图

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

# Example data
people = ('Tom', 'Dick', 'Harry', 'Slim', 'Jim')
y_pos = np.arange(len(people))
performance = 3 + 10 * np.random.rand(len(people))
error = np.random.rand(len(people))

fig, ax = plt.subplots()

hbars = ax.barh(y_pos, performance, xerr=error, align='center')
ax.set_yticks(y_pos, labels=people)
ax.invert_yaxis()  # labels read top-to-bottom
ax.set_xlabel('Performance')
ax.set_title('How fast do you want to go today?')

# Label with specially formatted floats
ax.bar_label(hbars, fmt='%.2f')
ax.set_xlim(right=15)  # adjust xlim to fit labels

plt.show()

使用条形标签可以做的一些更高级的事情

fig, ax = plt.subplots()

hbars = ax.barh(y_pos, performance, xerr=error, align='center')
ax.set_yticks(y_pos, labels=people)
ax.invert_yaxis()  # labels read top-to-bottom
ax.set_xlabel('Performance')
ax.set_title('How fast do you want to go today?')

# Label with given captions, custom padding and annotate options
ax.bar_label(hbars, labels=['±%.2f' % e for e in error],
             padding=8, color='b', fontsize=14)
ax.set_xlim(right=16)

plt.show()

参考

此示例中显示了以下函数、方法、类和模块的使用：

脚本总运行时间：（0分1.010秒）

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