在python中匹配一个dataframe和一个list时，如何克服缺少的值？

import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [6, 7, 8, 9, 10]})
lst = [1, 3, 5, 7, 9]

mask = df['A'].isin(lst)

filtered_df = df[mask]

reindexed_df = filtered_df.reindex(lst, fill_value=0)

import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [6, 7, 8, 9, 10]})
lst = [1, 3, 5, 7, 9]

mask = df['A'].isin(lst)
filtered_df = df[mask]
reindexed_df = filtered_df.reindex(lst, fill_value=0)

print(reindexed_df)

   A   B
0  1   6
2  3   8
4  5  10
1  0   0
3  0   0