Pandas DataFrame sum() method with examples

The sum() method in pandas calculates the sum of the values over the requested axis. This is equivalent to the method numpy.sum.

Examples –

Let’s create a dataset to work with.

import pandas as pd

data = {'Apple':[89, 89, 90, 110, 125, 84, 131, 123, 123, 140, 145, 145],
       'Orange': [46, 46, 50, 65, 63, 48, 110, 120, 60, 42, 47, 62],
       'Banana': [26, 30, 30, 25, 38, 22, 22, 36, 20, 27, 23, 34 ],
       'Mango': [80, 80, 90, 125, 130, 150, 140, 140, 135, 135, 80, 90]}

index = ['Jan','Feb','Mar','Apr','May','June','Jul','Aug','Sep','Oct','Nov','Dec']
df = pd.DataFrame(data, index=index)
df

1 . Calculate the Sum of the Columns –

You can calculate the sum of a single column like this

df['Apple'].sum()

#output
1394

or you can calculate the sum for all the columns like this

df.sum()

#output
Apple     1394
Orange     759
Banana     333
Mango     1375
dtype: int64

2 . Calculate the Sum of the Rows –

To calculate the sum of each rows, we need to set the axis parameter to axis=1 or columns.

df.sum(axis=1)

#output
Jan     241
Feb     245
Mar     260
Apr     325
May     356
June    304
Jul     403
Aug     419
Sep     338
Oct     344
Nov     295
Dec     331
dtype: int64