Most efficient way with Pandas to check pair of values from 2 series?

Question

Lets say I have a series/dataframe A that looks like

A = [3,2,1,5,4,...

A could also be sorted as it doesn't matter to me. I want to create a new series that keeps track of possible pairs. That is, I want the result to look like

B = [3_1, 3_2, 3_4, ..., 2_1, 2_4, ..., 1_4, 1_5,...

That is, I want to exclude 2_3 , since 3_2 already exists. I figure I could create each element in B using something like

for i in A:
    for j in A:
        s = A[i].astype(str) + '_' + A[j].astype(str)
        B.append(pd.Series([s]))

But I'm not sure how to make sure the (i,j) pairing doesn't already exist, such as making sure 2_3 doesn't get added as I mentioned above

What is the most efficient way to deal with this?

Answer 1

from itertools import combinations

s = pd.Series([1, 2, 3, 4])
s2 = pd.Series("_".join([str(a), str(b)]) for a, b in combinations(s, 2))

>>> s2
0    1_2
1    1_3
2    1_4
3    2_3
4    2_4
5    3_4
dtype: object

Answer 2

I don't think this really has much to do with pandas, except for the values originating (and possibly ending) in a series. Instead, I'd use itertools

Say you have an iterable a of values. Then

import itertools

set((str(i) + '_' + str(j)) for (i, j) in itertools.product(a, a) if i <= j)

will create a set of pairs where the integer before the _ is not larger than that after that, removing duplicates.

---

Example

import itertools

>>> set((str(i) + '_' + str(j)) for (i, j) in itertools.product(a, a) if i < j)
{'1_2',
 '1_3',
 '1_4',
 '1_6',
 '1_7',
 '2_3',
 '2_4',
 '2_6',
 '2_7',
 '3_4',
 '3_6',
 '3_7',
 '4_6',
 '4_7',
 '6_7'}

Answer 3

This can be done via a list comprehension:

>>> a = [3, 2, 1, 5, 4]
>>> [(str(x)+'_'+str(y)) for x in a for y in a if y>x]
['3_5', '3_4', '2_3', '2_5', '2_4', '1_3', '1_2', '1_5', '1_4', '4_5']

Note that the ordering of the members in the pairs in the result is sorted because of the y>x statement, which is why we have '1_3' in our output instead of '3_1' .

While importing itertools and using combinations is a correct way to do this, I usually prefer not to import libraries if I only need one one or two things from them that can also be easily accomplished via direct means.