查找两列都为NaN的观测值，并在pandas DataFrame中将其替换为0

import pandas as pd

df = pd.DataFrame({'A': [1, 2, float('nan')], 'B': [float('nan'), 5, float('nan')]})

mask = df['A'].isnull() & df['B'].isnull()

df.loc[mask, ['A', 'B']] = 0

import pandas as pd

df = pd.DataFrame({'A': [1, 2, float('nan')], 'B': [float('nan'), 5, float('nan')]})

mask = df['A'].isnull() & df['B'].isnull()
df.loc[mask, ['A', 'B']] = 0

print(df)

     A    B
0  1.0  NaN
1  2.0  5.0
2  0.0  0.0