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python - DataFrame sorting based on a function of multiple column values

Based on python, sort descending dataframe with pandas:

Given:

from pandas import DataFrame
import pandas as pd

d = {'x':[2,3,1,4,5],
     'y':[5,4,3,2,1],
     'letter':['a','a','b','b','c']}

df = DataFrame(d)

df then looks like this:

df:
      letter    x    y
    0      a    2    5
    1      a    3    4
    2      b    1    3
    3      b    4    2
    4      c    5    1

I would like to have something like:

f = lambda x,y: x**2 + y**2
test = df.sort(f('x', 'y'))

This should order the complete dataframe with respect to the sum of the squared values of column 'x' and 'y' and give me:

test:
      letter    x    y
    2      b    1    3
    3      b    4    2
    1      a    3    4
    4      c    5    1
    0      a    2    5

Ascending or descending order does not matter. Is there a nice and simple way to do that? I could not yet find a solution.

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You can create a temporary column to use in sort and then drop it:

df.assign(f = df['one']**2 + df['two']**2).sort_values('f').drop('f', axis=1)
Out: 
  letter  one  two
2      b    1    3
3      b    4    2
1      a    3    4
4      c    5    1
0      a    2    5

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