[英]Replace values dataframe python
如果需要替换NaN
值,则需要功能combine_first
或fillna
:
df['Clean Company Name'].combine_first(df['Company Name'])
要么:
df['Clean Company Name'].fillna(df['Company Name'])
样品:
df = pd.DataFrame({'Company Name':['s','d','f'], 'Clean Company Name': [np.nan, 'r', 't']})
print (df)
Clean Company Name Company Name
0 NaN s
1 r d
2 t f
#if need check NaNs
print (df['Clean Company Name'].isnull())
0 True
1 False
2 False
Name: Clean Company Name, dtype: bool
df['Clean Company Name'] = df['Clean Company Name'].combine_first(df['Company Name'])
print (df)
Clean Company Name Company Name
0 s s
1 r d
2 t f
编辑:
loc
条件替换数据,可以将loc
与boolean mask
一起使用:
print (df['Company Name'] == 'd')
0 False
1 True
2 False
Name: Company Name, dtype: bool
df.loc[df['Company Name'] == 'd', 'Clean Company Name'] = 'sss'
print (df)
Clean Company Name Company Name
0 NaN s
1 sss d
2 t f
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