np.where() do nothing if condition fails

Question

I have a sample from my dataframe:

       Created      Insert Time   MatchKey              In Previous    New Type
18593  2016-08-12   2018-02-19    LXGS0903         


        

Answer 1

You can use pd.Series.mask for exactly this purpose:

df['New Type'].mask(df['In Previous']=='Yes', 'In Previous', inplace=True)

Somewhat confusingly, you have to remember that pd.Series.mask updates a value when a condition is met, while pd.Series.where updates a value when a condition is not met.