creating new column based on condition (python)-CodePudding

I have a dataframe where one of the columns, "deals" is a TRUE/FALSE boolean. I want to create a new column that populates 1 when the "deals" column is True, and 0 when the "deals" columns is False.

I tried the following code but it's giving me all zeros. Please help

df['madedeal'] = np.where(df['deal']=='True', 1, 0)

CodePudding user response：

You can simply use astype(int) which converts True to 1 and False to 0 (no need for np.where here):

df['madedeal'] = df['deal'].astype(int)

CodePudding user response：

You have to compare with True, not "True" because "True" is str.

Also, it would be more recommended to use is when you compare with True or False rather than == (PEP 8: E712 comparison to True should be 'if cond is True:' or 'if cond:').

import pandas as pd
import numpy as np

df = pd.DataFrame({
    'deal': [True, False, True, False]
})

df['madedeal'] = np.where(df['deal'] is True, 1, 0)
# df['madedeal'] = np.where(df['deal'], 1, 0 # This also works as @sammywemmy commented.

print(df)

#    deal  madedeal
#0   True         1
#1  False         0
#2   True         1
#3  False         0