使用Pandas库中的groupby和plot方法对数据进行分组和绘图。

示例代码如下：

import pandas as pd import matplotlib.pyplot as plt

创建示例数据

data = {'name': ['Alice', 'Bob', 'Charlie', 'David', 'Emily', 'Fred'], 'gender': ['F', 'M', 'M', 'M', 'F', 'M'], 'age': [25, 32, 18, 47, 22, 19], 'salary': [50000, 70000, 40000, 90000, 35000, 60000]}

df = pd.DataFrame(data)

按性别分组并计算平均工资

grouped = df.groupby('gender')['salary'].mean()

绘制柱状图

grouped.plot(kind='bar') plt.title('Average Salary by Gender') plt.xlabel('Gender') plt.ylabel('Average Salary')

plt.show()

按年龄段分组并计算平均工资

bins = [18, 25, 35, 50, 65] labels = ['18-24', '25-34', '35-49', '50-64'] df['age_group'] = pd.cut(df['age'], bins=bins, labels=labels)

grouped = df.groupby('age_group')['salary'].mean()

绘制柱状图

grouped.plot(kind='bar') plt.title('Average Salary by Age Group') plt.xlabel('Age Group') plt.ylabel('Average Salary')

plt.show()