Build a dataframe based on new dataframe

I have a data frame with 9 columns (my real data is very big). I want to consider 4 by 4 columns and build a
new dataframe with 2 columns which shows the summation of those 4 columns. Here is a simple example:
I want to have the id column.

import pandas as pd
df = pd.DataFrame()
df['id'] = [1, 2, 3, 4]
df['a'] = [10, 0, 1, 3]
df['b'] = [-10, 0, 2, 2]
df['c'] = [0, 1, 3, 3]
df['d'] = [0, 0, 4, 4]
df['e'] = [10, 0, 1, 3]
df['f'] = [10, 0, 2, 2]
df['g'] = [0, -1, 0, 0]
df['h'] = [0, 0, 0, 0]
df

Answers:

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Method 1

You can use the underlying numpy array for an easy way to reshape:

a = df.drop(columns='id').to_numpy()
N = 4 # number of columns to group
df2 = pd.DataFrame(a.reshape((len(df), -1, N)).sum(2),
                   columns=[f'value{x+1}' for x in range(a.shape[1]//N)],
                   index=df['id']).reset_index()

output:

   id  value1  value2
0   1       0      20
1   2       1      -1
2   3      10       3
3   4      12       5

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