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Merging rows within a group together in Pandas

schedule Aug 12, 2023
Last updated
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To merge rows within a group together in Pandas we can use the agg(~) method together with the join(~) method to concatenate the row values.

Example

Consider the following DataFrame:

import pandas as pd

df = pd.DataFrame({"Name":["Mary","Sky","James"],"Hobbies":["Cooking","Travel","Cooking"]})
df
Name Hobbies
0 Mary Cooking
1 Sky Travel
2 James Cooking

To group by 'Hobbies' and merge names of all people with each hobby into a single row:

df.groupby('Hobbies', as_index=False).agg({'Hobbies' : 'first', 'Name' : ' '.join})
Hobbies Name
0 Cooking Mary James
1 Travel Sky

Notice how the names of people sharing the same hobby appear in a single line separated by ' '.

Specifying delimiter

We can specify the delimiter to use by placing it before the join(~) method like so:

df.groupby('Hobbies', as_index=False).agg({'Hobbies' : 'first', 'Name' : ', '.join})
Hobbies Name
0 Cooking Mary, James
1 Travel Sky

Here we specify the delimiter as a comma followed by a space.

robocat
Published by Arthur Yanagisawa
Edited by 0 others
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