pandas.factorize on an entire data frame

Question

pandas.factorize encodes input values as an enumerated type or categorical variable.

But how can I easily and efficiently convert many columns of a data frame? What

Answer 1

I also found this answer quite helpful: https://stackoverflow.com/a/20051631/4643212

I was trying to take values from an existing column in a Pandas DataFrame (a list of IP addresses named 'SrcIP') and map them to numerical values in a new column (named 'ID' in this example).

Solution:

df['ID'] = pd.factorize(df.SrcIP)[0]

Result:

        SrcIP | ID    
192.168.1.112 |  0  
192.168.1.112 |  0  
192.168.4.118 |  1 
192.168.1.112 |  0
192.168.4.118 |  1
192.168.5.122 |  2
192.168.5.122 |  2
...