Change and add values in dataframe depending on order ID

Question

So my table currently looks like this:

Roll No	Subject
1	Math
1	Science
2	History
2	Geography
2	Politics
3	FInance

Based on this I want to add a new column

Roll No	Subject	Details
1	Math	Other subject to Math
1	Science	Math to Science
2	History	Other subject to History
2	Geography	History to Geography
2	Politics	Geography to Politics
3	Finance	Other subject to Finance

I am really confused as to how this would be. I am able to write the first instance of a roll no as "Other subject to xyz" but cannot seem to understand how the following values will carry over. Thank you

Asked By: Hey there

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Source

Answer 1

Using df.groupby() and .transform() methods with lambda

df["Details"] = (df.groupby("Roll No")
                    .Subject.transform(lambda x: x.shift()
                    .add(" to ").fillna("Other subject to ") + x))
print(df)

   Roll No    Subject                   Details
0        1       Math     Other subject to Math
1        1    Science           Math to Science
2        2    History  Other subject to History
3        2  Geography      History to Geography
4        2   Politics     Geography to Politics
5        3    Finance  Other subject to Finance

Answered By: Jamiu S.

Answer 2

You can use only pandas.DataFrame.shift on columns "Roll No", "Subject" then use numpy.where.

import numpy as np

ss = df['Subject'].shift()
sr = df['Roll No'].shift()
r1 = ss + ' to ' + df['Subject']
r2 = 'Other subject to ' + df['Subject']
df['res'] = np.where(sr==df['Roll No'], r1, r2)
print(df)

Output:

   Roll No    Subject                       res
0        1       Math     Other subject to Math
1        1    Science           Math to Science
2        2    History  Other subject to History
3        2  Geography      History to Geography
4        2   Politics     Geography to Politics
5        3    FInance  Other subject to FInance

Answered By: I'mahdi

Change and add values in dataframe depending on order ID

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