使用Python库绘制共享相同y轴的两个水平条形图

Question

我想绘制两个共享相同y轴的水平条形图.例如,以下问题显示了如何在R中实现此目的:

ggplot2中共享轴的两个水平条形图(类似于人口金字塔)

如何用Python创建类似的情节？

上面问题的情节如下:

以下是上图中使用的状态列表(y轴):

["AK", "TX", "CA", "MT", "NM", "AZ", "NV", "CO", "OR", "WY", 
 "MI", "MN", "UT", "ID", "KS", "NE", "SD", "WA", "ND", "OK"]

以下是每个州的销售人员数量列表:

[20,30,40,10,15,35,18,25,22,7,12,22,3,4,5,8,14,28,24,32]

销售数字可以是随机的.

Answer 1

一般来说,如果您显示的两个变量位于不同的单位或具有不同的范围,那么您将需要使用两个具有共享y轴的子图.这类似于@regdoug的答案,但最好明确地共享y轴以确保数据保持对齐(例如,尝试使用此示例进行缩放/平移).

例如:

import matplotlib.pyplot as plt

y = range(20)
x1 = range(20)
x2 = range(0, 200, 10)

fig, axes = plt.subplots(ncols=2, sharey=True)
axes[0].barh(y, x1, align='center', color='gray')
axes[1].barh(y, x2, align='center', color='gray')
axes[0].invert_xaxis()
plt.show()

如果你想更精确地重现你链接到的问题中显示的例子(我将离开灰色背景和白色网格,但如果你喜欢它们,那么很容易添加):

import numpy as np
import matplotlib.pyplot as plt

# Data
states = ["AK", "TX", "CA", "MT", "NM", "AZ", "NV", "CO", "OR", "WY", "MI",
          "MN", "UT", "ID", "KS", "NE", "SD", "WA", "ND", "OK"]
staff = np.array([20, 30, 40, 10, 15, 35, 18, 25, 22, 7, 12, 22, 3, 4, 5, 8,
                  14, 28, 24, 32])
sales = staff * (20 + 10 * np.random.random(staff.size))

# Sort by number of sales staff
idx = staff.argsort()
states, staff, sales = [np.take(x, idx) for x in [states, staff, sales]]

y = np.arange(sales.size)

fig, axes = plt.subplots(ncols=2, sharey=True)
axes[0].barh(y, staff, align='center', color='gray', zorder=10)
axes[0].set(title='Number of sales staff')
axes[1].barh(y, sales, align='center', color='gray', zorder=10)
axes[1].set(title='Sales (x $1000)')

axes[0].invert_xaxis()
axes[0].set(yticks=y, yticklabels=states)
axes[0].yaxis.tick_right()

for ax in axes.flat:
    ax.margins(0.03)
    ax.grid(True)

fig.tight_layout()
fig.subplots_adjust(wspace=0.09)
plt.show()

一个警告.我没有真正正确对齐y-tick-labels.有可能做到这一点,但它比你想象的更痛苦.因此,如果你真的想要总是在图中间完全居中的y-tick-labels,最简单的方法是以不同的方式绘制它们.而不是axes[0].set(yticks=y, yticklabels=states),你做的事情如下:

axes[0].set(yticks=y, yticklabels=[])
for yloc, state in zip(y, states):
    axes[0].annotate(state, (0.5, yloc), xycoords=('figure fraction', 'data'),
                     ha='center', va='center')