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

1 Answers

0
jezrael On

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()