如何在matplotlib中的“我的绘图”中添加其他标签？

Question

我想要像照片上那样的东西

这是我的密码：

import matplotlib.pyplot as plt
import pandas as pd

plt.style.use('seaborn-notebook')

data = {
    'Unmarried woman': [36, 23, 28, 20, 16],
    'Married woman': [26, 38, 49, 14, 38]
}

unmarried_labels = ['30–55', '14–50', '16-59', '16-24', '13-26']
married_labels = ['25–50', '29–59', '34–89', '11–18', '33–55']

df = pd.DataFrame(data, columns=['Unmarried woman', 'Married woman'],
                  index=['Africa', 'Asia', 'Latin America', 'Northern America',
                         'Europe'])

df.plot.barh()

plt.title(
    'Abortion rate per 1000 women aged 15–44 y. by marital status (2010–2014)',
    fontweight='bold', fontsize=11)

plt.show() 

Answer 1

从Matplotlib 3.4.0开始，这可以通过^{}和带标签的压缩容器来实现：

# Save axes returned from DataFrame plot
ax = df.plot.barh()
# Iterate over containers and all_labels together
for container, labels in zip(ax.containers, all_labels):
    ax.bar_label(container, labels=labels, label_type='center')

• 标签将与数据框的索引对齐：
  • all_labels中的第一个列表将与列0（Unmarried woman）对齐，并在列之间继续
  • 每个子列表（labels）中的索引0将与数据帧中的索引0对齐，即Africa，并继续向下移动行

---

总而言之：

import matplotlib.pyplot as plt
import pandas as pd

plt.style.use('seaborn-notebook')

unmarried_labels = ['30–55', '14–50', '16-59', '16-24', '13-26']
married_labels = ['25–50', '29–59', '34–89', '11–18', '33–55']
all_labels = [unmarried_labels, married_labels]

df = pd.DataFrame({'Unmarried woman': [36, 23, 28, 20, 16],
                   'Married woman': [26, 38, 49, 14, 38]},
                  columns=['Unmarried woman', 'Married woman'],
                  index=['Africa', 'Asia', 'Latin America', 'Northern America',
                         'Europe'])

# Save axes returned from DataFrame plot
ax = df.plot.barh()
# Iterate over containers and all_labels together
for container, labels in zip(ax.containers, all_labels):
    ax.bar_label(container, labels=labels, label_type='center')

plt.title(
    'Abortion rate per 1000 women aged 15–44 y. by marital status (2010–2014)',
    fontweight='bold',
    fontsize=11
)

plt.tight_layout()
plt.show()