Sum columns values with common values in another column

Question

I have this dataframe:

I want to sum all the distances that have been done each day, giving the next dataframe:

distances = [
    (32.2,1),
    (40.2,1),
    (22.5,2),
    (37.6,2),
    (5.6,2),
    (5.8,3),
    (9.7,3),
    (10.2,3),
    (12.3,4),
    (15.2,4),
]
             
expected_result = [
    (72.5,1),
    (65.5,2),
    (25.7,3),
    (27.5,4),
]
             
distances = pd.DataFrame(distances, columns = ['distance','day'])
expected_result = pd.DataFrame(expected_result, columns = ['distance','day'])

I’m new to pandas so I don’t know exactly how to do it.

Asked By: Sergio

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Source

Answer 1

You can group the data by "day" then sum it

distances = distances.groupby('day').sum()

If you want to sort the data according to distance you can use this

distances = distances.sort_values(by=['distance'], ascending=False)

Answered By: xFranko

Answer 2

use groupby

data="""distance    day
32.2    1
40.2    1
22.5    2
37.6    2
5.6 2
5.8 3
9.7 3
10.2    3
12.3    4
15.2    4
"""
print("Sum by day")

import pandas as pd

df = pd.read_csv(StringIO(data), sep='t')

df.groupby('day').sum()

output:

distance
day 
1   72.4
2   65.7
3   25.7
4   27.5

Answered By: Golden Lion

Sum columns values with common values in another column

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