Change pandas dataframe column value depending on other columns values having three options-CodePudding

I have a Pandas dataframe with a column named col1, and I want to add a new column to the dataframe, which value depends on the content of col1 for each record. I tried this:

d['new_column'] = 'CASE 1' if d['COL1'] == None else 'CASE 2' if d['COL1'] == 0 else 'CASE 3'

But I got this error:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

How can I make the evaluation to set the values of the new column properly?

CodePudding user response：

Try using np.where. It's efficient and easy to use for this cases:

import numpy as np

df['new_column'] = np.where(d['COL1'].isnull(), 'CASE1',
                            np.where(d['COL1']==0, 'CASE 2', 'CASE 3'))