问题描述
我刚开始使用 matplotlib.pyplot 并且有点卡住了.
I am just starting out with matplotlib.pyplot and am a little stuck.
使用matpltlib.pyplot文档中的示例,我创建了一个堆积的条形图使用以下代码:
Using the example in the matpltlib.pyplot documentation, I have created a stacked bar chart using the following code:
import numpy as np
import matplotlib.pyplot as plt
N = 7
OECD = (242, 244, 255, 263, 269, 276, 285)
NonOECD = (282, 328, 375, 417, 460, 501, 535)
Sum = ('524', '572', '630', '680', '729', '777', '820')
ind = np.arange(N)
width = 0.5
p1 = plt.bar(ind, NonOECD, width, color = 'r')
p2 = plt.bar(ind, OECD, width, color = 'b', bottom = NonOECD)
plt.ylabel('Quadrillion Btu')
plt.title('World Total Energy Consumption 2010 - 2040')
plt.xticks(ind+width/2., ('2010', '2015', '2020', '2025', '2030', '2035', '2040'))
plt.yticks(np.arange(0, 1001, 200))
plt.legend((p1[0], p2[0]), ('Non - OECD', 'OECD'), loc = 2, frameon = 'false')
plt.tick_params(top = 'off', bottom = 'off', right = 'off')
plt.grid(axis = 'y', linestyle = '-')
plt.show()
但是我想在条形顶部显示总数,但我无法弄清楚如何.我见过 这篇文章但我遇到了问题:
However I want to display the totals on top of the bars and I cannot quite work out how. I have seen this post but am having issues:
for ii,rect in enumerate(p1):
h1 = rect.get_height()
for ii,rect in enumerate(p2):
h2 = rect.get_height()
height =
plt.text(rect.get_x()+rect.get_width()/2., height, '%s'% (Sum[ii]), ha = 'center', va='bottom')
如果我使用 height = h1
,则会得到;如果我使用 height = h2
,则会得到;如果我使用 height = h1 + h2
我得到 .
If I use height = h1
I get ; if I use height = h2
I get ; if I use height = h1 + h2
I get .
我想要的是这些数字直接位于第二个(蓝色)柱上方(例如我第一次尝试中2010年柱上的524).我是否遗漏了一些非常明显的东西?
What I want is these numbers sitting directly on above the second (blue) bar [like the 524 on the 2010 bar in my 1st attempt]. Am I missing something really obvious?
一如既往,任何帮助将不胜感激!干杯
As always, any help would be much appreciated!Cheers
推荐答案
尝试一下:
for r1,r2 in zip(p1,p2):
h1 = r1.get_height()
h2 = r2.get_height()
plt.text(r1.get_x()+r1.get_width()/2., h1+h2, '%s'% (h1+h2), ha = 'center', va='bottom')
这篇关于在条形图中显示堆叠条形上方的总数:matplotlib.pyplot的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!