pandas replace boolean value with string or integer

Question

This is snipett of my code with column values comparison:

import pandas as pd
df =pd.DataFrame({'coname1':['Apple','Yahoo','Gap Inc'],'coname2':['Apple', 'Google', 'Apple']})
df['eq'] =df.apply(lambda row: row['coname1'] == row['coname2'],axis=1)

The problem is that I am interested with Character (True='Y' or False = 'N') or Integer (True= 1 or False = 0) values.

Option df.replace(['True', 'False'],[1,0]) doesn't work Thank you

pass a dict to use replace on the df: df.replace({'True':1,'False':0}) — EdChum
– EdChum, Commented Sep 26, 2016 at 9:11
You could also do this in your function itself: df['eq'] = df.apply(lambda row: 1 if row['coname1'] == row['coname2'] else 0, axis=1) — Nickil Maveli
– Nickil Maveli, Commented Sep 26, 2016 at 9:16
I've been struggling with replace boolean values with integer too! converting a boolean call to int seems to be the best way, right now, if you want 0 or 1 — fixxxer
– fixxxer, Commented Apr 5, 2017 at 10:25

piRSquared · Accepted Answer · 2016-09-26 09:11:19Z

19

When assigning the 'eq' column, use atype(int). The int conversion turns True into 1 and False into 0

df = pd.DataFrame({'coname1': ['Apple','Yahoo','Gap Inc'], 'coname2':['Apple', 'Google', 'Apple']})
df['eq'] = df.apply(lambda row: row['coname1'] == row['coname2'], axis=1).astype(int)

For characters

df['eq'] = np.where(df['eq'], 'Y', 'N')
df

edited Sep 26, 2016 at 9:11

answered Sep 26, 2016 at 9:07

piRSquared

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pds Over a year ago

typo in line 1. astype() .. panda docs

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