Mapping values in place (for example with Gender) from string to int in Pandas dataframe [duplicate]

Answer 1

Another solution you can use with np.where:

Just an example DataFrame:

>>> df
      Sex
0    male
1  female
2  female
3  female
4    male

Based on the condition create new column new_Sex

>>> df['new_Sex'] = np.where(df['Sex'] == 'male', 0, 1)
>>> df
      Sex  new_Sex
0    male        0
1  female        1
2  female        1
3  female        1
4    male        0

OR:

>>> df['new_Sex'] = np.where(df['Sex'] != 'male', 1, 0)
>>> df
      Sex  new_Sex
0    male        0
1  female        1
2  female        1
3  female        1
4    male        0