我有名为df
具有原始形状(4361, 15)
。一些agefm
列的值为 NaN。只是看看:
> df[df.agefm.isnull() == True].agefm.shape
(2282,)
然后我创建新列并将其所有值设置为 0:
df['nevermarr'] = 0
所以我想设置nevermarr
值为 1,然后在该行中agefm
is Nan:
df[df.agefm.isnull() == True].nevermarr = 1
没有改变:
> df['nevermarr'].sum()
0
我究竟做错了什么?
最好的就是使用numpy.where:
df['nevermarr'] = np.where(df.agefm.isnull(), 1, 0)
print (df)
agefm nevermarr
0 NaN 1
1 5.0 0
2 6.0 0
Or use loc, ==True
可以省略:
df.loc[df.agefm.isnull(), 'nevermarr'] = 1
Or mask:
df['nevermarr'] = df.nevermarr.mask(df.agefm.isnull(), 1)
print (df)
agefm nevermarr
0 NaN 1
1 5.0 2
2 6.0 3
Sample:
import pandas as pd
import numpy as np
df = pd.DataFrame({'nevermarr':[7,2,3],
'agefm':[np.nan,5,6]})
print (df)
agefm nevermarr
0 NaN 7
1 5.0 2
2 6.0 3
df.loc[df.agefm.isnull(), 'nevermarr'] = 1
print (df)
agefm nevermarr
0 NaN 1
1 5.0 2
2 6.0 3
本文内容由网友自发贡献,版权归原作者所有,本站不承担相应法律责任。如您发现有涉嫌抄袭侵权的内容,请联系:hwhale#tublm.com(使用前将#替换为@)