Matplotlib - 如何为图例添加标签

Question

在这里，我试图通过在 x 轴上绘制年龄和在 y 轴上绘制票价来将数据与男性因素分开，我想在图例中显示两个标签，用各自的颜色区分男性和女性。谁能帮我做这。代码：import matplotlib.pyplot as pltimport pandas as pddf = pd.read_csv('https://sololearn.com/uploads/files/titanic.csv')df['male']=df['Sex']=='male'sc1= plt.scatter(df['Age'],df['Fare'],c=df['male'])plt.legend()plt.show()

Answer 1

您可以使用seaborn构建在其之上的库matplotlib来执行您需要的确切任务。只需传入中的参数，即可绘制'Age'vs散点图'Fare'并对其进行颜色编码，如下所示：'Sex'huesns.scatterplot

import matplotlib.pyplot as plt

import seaborn as sns

plt.figure()

# No need to call plt.legend, seaborn will generate the labels and legend

# automatically.

sns.scatterplot(df['Age'], df['Fare'], hue=df['Sex'])

plt.show()

Seaborn 用更少的代码和更多的功能生成更好的图。

您可以seaborn使用pip install seaborn.

Answer 2

PathCollection.legend_elements方法可用于控制要创建多少图例条目以及如何标记它们。

import matplotlib.pyplot as plt

import pandas as pd

df = pd.read_csv('https://sololearn.com/uploads/files/titanic.csv')

df['male'] = df['Sex']=='male'

sc1= plt.scatter(df['Age'], df['Fare'], c=df['male'])

plt.legend(handles=sc1.legend_elements()[0], labels=['male', 'female'])

plt.show()

Answer 3

这可以通过将数据隔离在两个单独的数据框中来实现，然后可以为这些数据框设置标签。

import matplotlib.pyplot as plt

import pandas as pd

df = pd.read_csv('https://sololearn.com/uploads/files/titanic.csv')

subset1 = df[(df['Sex'] == 'male')]

subset2 = df[(df['Sex'] != 'male')]

plt.scatter(subset1['Age'], subset1['Fare'], label = 'Male')

plt.scatter(subset2['Age'], subset2['Fare'], label = 'Female')

plt.legend()

plt.show()