How to iterate over pandas rows to make a new column using conditions?

Asked Mar 12 '20 at 12:51

Active Mar 12 '20 at 12:51

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I have a dataframe that looks something like:

index   A   ... pheno
0      0.8        0
:
500000 1.4        5

where pheno is a int between 0 and 5.

I want to iterate over the rows and check the pheno column and create a new column based on the value in pheno, so if pheno is 0 then the new column class will be 1.

so:

index   A  ...  pheno  class
0      0.8        0      1
:
500000 1.4        5      3

I know how to do this using df.iterrows and if/elif but was wondering if there was a quicker way than generating 5 elif statements for each pheno value?

Just to add - in some cases my pheno column can be up to 13+ values hence why I think if/elif are inefficient.

asked Mar 12 '20 at 12:51

startswithH

Do you need [map](https://stackoverflow.com/q/24216425) ? – jezrael Mar 12 '20 at 12:54
Can you create [minimal, complete, and verifiable example](http://stackoverflow.com/help/mcve) ? – jezrael Mar 12 '20 at 12:54
Yes ```map``` is what I needed! Thank you! – startswithH Mar 12 '20 at 12:55

How to iterate over pandas rows to make a new column using conditions?

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