替换值数据框 python

Replace values dataframe python

我想替换数据框中满足条件的一些值。 我尝试编写代码但似乎不起作用

dfa = df.copy()

for value in df['Clean Company Name']:
    if value=="NaN":
        dfa['Clean Company Name'].replace(df['Company Name'])


dfa.head()

如您所见,NaN 值未被 'Company Name'

替换

我如何实现该结果?

如果需要替换 NaN 值需要函数 combine_first or fillna:

df['Clean Company Name'].combine_first(df['Company Name'])

或:

df['Clean Company Name'].fillna(df['Company Name'])

样本:

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

更多关于 missing data

编辑:

对于按条件替换数据是可能的,使用 locboolean mask:

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