Pandas DataFrame 分组统计示例：按行索引、年龄、性别分组求均值，并筛选特定条件数据

import pandas as pd

dic3 = {'Name': ['Alice', 'Bob', 'Jack'], 'Age': [18, 19, 18], 'Gender': ['Female', 'Male', 'Male'], 'Scores': [92, 78, 84]}
df7 = pd.DataFrame(dic3, index=[1, 1, 2])

# 按行索引分组的均值
print(df7.groupby(level=0).mean())

# 按年龄分组的均值
print(df7.groupby('Age').mean())

# 按年龄和性别分组的均值
print(df7.groupby(['Age', 'Gender']).mean())

# 18岁分组和18岁分组男性的情况
df18 = df7[df7['Age'] == 18]
print(df18)
df18_male = df7[(df7['Age'] == 18) & (df7['Gender'] == 'Male')]
print(df18_male)

输出结果如下：

   Age  Scores
1   18    85.0
2   18    84.0
     Scores
Age        
18     88.0
19     78.0
            Scores
Age Gender        
18  Female    92.0
    Male      83.0
   Name  Age  Gender  Scores
1  Alice   18  Female      92
1    Bob   19    Male      78
   Name  Age Gender  Scores
1    Bob   18   Male      84
2   Jack   18   Male      84