如何在pandas中使用一个数据帧的索引来重新索引另一个数据帧

import pandas as pd

# 创建两个示例数据帧
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, index=[0, 1, 2])
df2 = pd.DataFrame({'C': [7, 8, 9], 'D': [10, 11, 12]}, index=[0, 2, 3])

# 使用df2的索引对df1进行重新索引
df1_reindexed = df1.reindex(df2.index)

print(df1_reindexed)

     A    B
0  1.0  4.0
2  3.0  6.0
3  NaN  NaN

import pandas as pd

# 创建两个示例数据帧
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, index=[0, 1, 2])
df2 = pd.DataFrame({'C': [7, 8, 9], 'D': [10, 11, 12]}, index=[0, 2, 3])

# 使用df2的索引选择对应行的数据
df1_reindexed = df1.loc[df2.index]

print(df1_reindexed)

   A  B
0  1  4
2  3  6
3  NaN NaN

import pandas as pd

# 创建两个示例数据帧
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, index=[0, 1, 2])
df2 = pd.DataFrame({'C': [7, 8, 9], 'D': [10, 11, 12]}, index=[0, 2, 3])

# 使用df2的索引对df1进行重新索引
df1_reindexed = df1.reindex_like(df2)

print(df1_reindexed)

     A    B
0  1.0  4.0
2  3.0  6.0
3  NaN  NaN