你需要使用DataFrame.loc,因为通过标签选择Bike
and Mileage
:
d2 = df.loc[pd.isnull(df['Mileage']),['Bike','Mileage']]
Or use Series.isna:
d2 = df.loc[df['Mileage'].isna(),['Bike','Mileage']]
If need DataFrame.iloc需要将布尔掩码转换为 numpy 数组,还需要将列转换为列的位置Index.get_indexer:
d2 = df.iloc[pd.isnull(df['Mileage']).values, df.columns.get_indexer(['Bike','Mileage'])]
Sample:
df = pd.DataFrame({
'A':list('abcdef'),
'Mileage':[np.nan,5,4,5,5,np.nan],
'Bike':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
})
print (df)
A Mileage Bike D E F
0 a NaN 7 1 5 a
1 b 5.0 8 3 3 a
2 c 4.0 9 5 6 a
3 d 5.0 4 7 9 b
4 e 5.0 2 1 2 b
5 f NaN 3 0 4 b
d2 = df.loc[pd.isnull(df['Mileage']),['Bike','Mileage']]
print (d2)
Bike Mileage
0 7 NaN
5 3 NaN
d2 = df.iloc[pd.isnull(df['Mileage']).values, df.columns.get_indexer(['Bike','Mileage'])]
print (d2)
Bike Mileage
0 7 NaN
5 3 NaN