我有一个数据帧:
subtracted Subs hrs
0 281871.120 450878.77 0.00
1 221343.432 229535.34 0.00
2 197454.408 32080.93 0.00
3 41934.000 -9853.07 32080.93
我想从减去列到hrs列替换正值(相对于子列)。
预期产量:
subtracted Subs hrs
0 281871.120 450878.77 281871.120
1 221343.432 229535.34 221343.432
2 197454.408 32080.93 197454.408
3 41934.000 -9853.07 32080.93
任何人都可以建议我这样做的正确方法吗?
您可以使用loc
,where
或numpy.where
替换为正值创建的掩码:
m = df['Subs'] > 0
df.loc[m, 'hrs'] = df['subtracted']
df['hrs'] = df['subtracted'].where(m, df['hrs'])
df['hrs'] = np.where(m, df['subtracted'], df['hrs'])
print (df)
subtracted Subs hrs
0 281871.120 450878.77 281871.120
1 221343.432 229535.34 221343.432
2 197454.408 32080.93 197454.408
3 41934.000 -9853.07 32080.930
对于由负值创建的掩码,可以使用mask
:
m = df['Subs'] < 0
df['hrs'] = np.where(m, df['hrs'], df['subtracted'])
df['hrs'] = df['subtracted'].mask(m, df['hrs'])