How to use if else type condition in DataFrame without loop?

Question

I have a DataFrame df:

I want: if Date1> Date2, then id1 else id2

Output:

How to complete this without using loops? Any hints pls

What do you want to do after choosing id1 or id2? You can use df.apply — Mayank Porwal
– Mayank Porwal, Commented Feb 17, 2022 at 5:03

Mayank Porwal · Accepted Answer · 2022-02-17 05:07:21Z

3

You can use numpy.where:

import numpy as np

df['output'] = np.where(df['Date1'].gt(df['Date2']), df['Id1'], df['Id2'])

answered Feb 17, 2022 at 5:07

Mayank Porwal

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Comments

Rajarshi Ghosh · Accepted Answer · 2022-02-17 05:11:23Z

0

Steps -

Convert the date1 and date2 to datetime object using the pd.to_datetime()

df['date1'] = pd.to_datetime( df.date1)
df['date2'] = pd.to_datetime( df.date2)

Initialize an empty numpy array and then iterate through the rows using df.iterrows() getting proper values into the numpy array and then add a new column.

import numpy as np
n = np.empty(len(df))

for row in df.iterrows():

    # row[1] has the row data
    # row[0] has the index

    if row[1]['date1'] > row[1]['date2']:
        n[row[0]] = 1
    else:
        n[row[0]] = 0
df['output'] = n

There are short hands for this code as well.

answered Feb 17, 2022 at 5:11

Rajarshi Ghosh

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2 Comments

Ussu20 Over a year ago

thanks. I am looking for the short hand code

Rajarshi Ghosh Over a year ago

one provided by @Mayank Porwal is good

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