考虑来自 matplotlib 网站的这个示例代码:
# a stacked bar plot with errorbars
import numpy as np
import matplotlib.pyplot as plt
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
p1 = plt.bar(ind, menMeans, width, color='#d62728', yerr=menStd)
p2 = plt.bar(ind, womenMeans, width,
bottom=menMeans, yerr=womenStd)
plt.ylabel('Scores')
plt.title('Scores by group and gender')
plt.xticks(ind, ('G1', 'G2', 'G3', 'G4', 'G5'))
plt.yticks(np.arange(0, 81, 10))
plt.legend((p1[0], p2[0]), ('Men', 'Women'))
plt.show()
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假设我有第三个系列并且我希望将其堆叠在顶部。如何表达一个
bottom
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范围?我试着简单地做
menMeans + womenMeans
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但这没有用。
来源:https : //matplotlib.org/2.0.0/examples/pylab_examples/bar_stacked.html
原则上你是正确的:你需要将前一个柱的高度相加才能获得bottom下一个柱的高度。
问题是你不能简单地添加元组。所以一个好主意是将它们制作为numpy数组menMeans = np.array(menMeans)。
这些numpy数组可以很容易地添加在一起,这样
p3 = plt.bar(ind, childrenMeans, width, bottom=menMeans+womenMeans)
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效果很好。
完整代码:
import numpy as np
import matplotlib.pyplot as plt
menMeans = np.array((20, 35, 30, 35, 27))
womenMeans = np.array((25, 32, 34, 20, 25))
childrenMeans = np.array((21, 30, 32, 10, 36))
ind = np.arange(5)
width = 0.35
p1 = plt.bar(ind, menMeans, width, color='#d62728', )
p2 = plt.bar(ind, womenMeans, width, bottom=menMeans)
p3 = plt.bar(ind, childrenMeans, width, bottom=menMeans+womenMeans)
plt.ylabel('Scores')
plt.title('Scores by group and gender')
plt.xticks(ind, ('G1', 'G2', 'G3', 'G4', 'G5'))
plt.yticks(np.arange(0, 81, 10))
plt.legend((p1[0], p2[0], p3[0]), ('Men', 'Women', "Children"))
plt.show()
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