I have a logical column
df['Employed'].dtypes
Out[3]: dtype('O')
values showing
df['Employed'].value_counts()
Out[4]:
False 156133
True 13271
Name: Self_Employed2, dtype: int64
unique showing nan
df['Employed'].unique()
Out[5]:array([nan, False, True], dtype=object)
Number of missing
df['Employed'].isnull().sum()
Out[6]: 21210
I am trying to convert logical to string and change 'nan' to 'False', then Change 'False' to 'No' and 'True' to 'Yes', Triied to convert 'nan' as 'False' using fillna(False), its not working Tried using str.replace('False','No') that's also not working
I need
Out[7]:
False 177343
True 13271
Name: Employed, dtype: int64
You can use try replace missing values by Series.fillna
with False
without '
for boolean:
df.Employed = df.Employed.fillna(False)
Or remove missing values by Series.dropna
:
df.Employed = df.Employed.dropna()
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.