替换值dataframe python

Question

我想替换符合条件的数据框中的某些值。 我试着编写代码，但似乎没有工作

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＆＃39;公司名称替换​​

我如何实现这一结果？

Answer 1

如果需要替换NaN值需要函数combine_first或fillna：

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

或者：

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

有关missing data的更多信息。

编辑：

对于按条件替换数据，可以使用loc与boolean 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