pandas中分类级别的合并级别

import pandas as pd

# 创建series1
series1 = pd.Series([1, 2, 3], index=pd.CategoricalIndex(['A', 'B', 'C'], categories=['A', 'B', 'C', 'D']))

# 创建series2
series2 = pd.Series([4, 5, 6], index=pd.CategoricalIndex(['C', 'D', 'E'], categories=['C', 'D', 'E', 'F']))

# 合并两个Series
merged_series = pd.concat([series1, series2], keys=['Series1', 'Series2'])

# 查看合并后的Series
print(merged_series)

Series1  A    1
         B    2
         C    3
Series2  C    4
         D    5
         E    6
dtype: int64

# 选择第一层级为'Series1'，第二层级为'C'的值
print(merged_series.loc['Series1', 'C'])

3

# 将合并后的Series转换为分类类型
merged_series = merged_series.astype('category', categories=['A', 'B', 'C', 'D', 'E', 'F'])

# 查看转换后的Series
print(merged_series)

Series1  A    1
         B    2
         C    3
Series2  C    4
         D    5
         E    6
dtype: category
Categories (6, object): ['A', 'B', 'C', 'D', 'E', 'F']