Creating custom names for columns based on other column names in pandas dataframe

Question

I have a dataframe like below:

I am looking to create a column using difference or use any other calculations among columns. However, I looking to name the column so that it relfects the operation done. For ex below I am finding the difference b/w Origin 1 and Dest 1 as below:

How do I create those custom naming of columns as highlighted and especially when I have to create multiple such columns.

Answer 1

Just iterate through it and for naming you can use a f-string

for col_a in df.columns:
   for col_b in df.columns:
      if col_a != col_b:
         df[f'{col_a} - {col_b}'] = df[col_a] - df[col_b]

if you use itertools (pre-installed in python) you can make it easier to read (as proposed by @MustafaAydın):

import itertools
for col_a, col_b in itertools.permutations(df, 2):
    df[f'{col_a} - {col_b}'] = df[col_a] - df[col_b]

if you want to do multiple operations just add a line

import itertools
for col_a, col_b in itertools.permutations(df, 2):
    df[f'{col_a} - {col_b}'] = df[col_a] - df[col_b]
    df[f'{col_a} + {col_b}'] = df[col_a] + df[col_b]

if you only want to use subsets of columns, e.g. only from origin to destination you can do:

import itertools
origins = [col for col in df.columns if col.startswith('Origin')]
destinations = [col for col in df.columns if col.startswith('Dest')]
for col_a, col_b in itertools.product(origins, destinations):
    df[f'{col_a} - {col_b}'] = df[col_a] - df[col_b]
    df[f'{col_a} + {col_b}'] = df[col_a] + df[col_b]