CODEWITHSUNDEEP
pythonpandasdataframe
eweiss1997
eweiss1997

Reputation: 27

Boolean on a dataframe

Hey guys not sure if what I am trying to do is possible but I want to make a new column in a dataframe based on whether the string says 'complete'. if it does i want the new column row to say 1 if not 0. Since I have many records i put it in a loop.

august_report['Lease'] = np.nan
for x in august_report.iterrows():
    if august_report['Transaction Types'] =='Matched Lease transaction':
        august_report['Lease'] = '1'
    else:
        august_report['Lease'] = '0'

Upvotes: 0

Views: 59

Answers (3)

Derek Eden
Derek Eden

Reputation: 4618

can apply a lambda

df['Lease'] = df['Transaction Types'].apply(lambda x: '1' if x == 'Matched Lease transaction' else '0')

Upvotes: 0

willeM_ Van Onsem
willeM_ Van Onsem

Reputation: 476534

Yes, you can assign values to a column like:

august_report['Lease'] = august_report['Transaction Types'].eq('Matched Lease transaction').astype(int)

Probably a numerical 0 and 1 are better here (or even False and True, by dropping the .astype(int)), since that shows that we are dealing with numerical data, not text data.

Upvotes: 0

ParalysisByAnalysis
ParalysisByAnalysis

Reputation: 733

Numpy provides an easy way to do this if you have two values like your example (using np.where). If you have multiple cases, look at np.select.

import numpy as np
august_report['Lease'] = np.where(august_report['Transaction Types'] =='Matched Lease transaction', '1','0')

Upvotes: 1

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