Group Elements at Same Indices in a Multi-List - Python

We are given a 2D list, we have to group elements at the same indices in a multi-list which means combining elements that are positioned at identical indices across different list. For example:
If we have a 2D list: [[1, 2, 3], [4, 5, 6], [7, 8, 9]] then grouping elements at the same indices would result in [(1, 4, 7), (2, 5, 8), (3, 6, 9)].

Using zip() 

zip() function combines elements from multiple lists at matching indices into tuples. Given a 2D list [[1, 2, 3], [4, 5, 6], [7, 8, 9]] zip() creates pairs by taking elements at index 0 from each sublist thus resulting in [(1,4,7), (2,5,8), (3,6,9)].

li = [[1, 4, 5], [4, 6, 8], [8, 3, 10]]

print("Original list : " + str(li))

# using list comprehension and zip() to pair index elements
res = [list(x) for x in zip(*li)]

print("Index pairs list : " + str(res))

Original list : [[1, 4, 5], [4, 6, 8], [8, 3, 10]]
Index pairs list : [[1, 4, 8], [4, 6, 3], [5, 8, 10]]

Explanation:

• zip(*li) unpacks the lists inside l and pairs the elements at the same indices thus creating tuples.
• list comprehension [list(x) for x in ...] converts these tuples into lists which results in a new list where each sub-list contains elements from the same index of all input lists.

Let's explore other methods for achieving the same:

Using map() Function

map() function pairs up elements from multiple lists by applying a custom function to matching elements at each index position. It takes your function and runs it on corresponding items across all the lists at once.

li = [[1, 4, 5], [4, 6, 8], [8, 3, 10]]

# using map() to pair index elements
res = list(map(list, zip(*li)))

print("Index pairs list : " + str(res))

Original list : [[1, 4, 5], [4, 6, 8], [8, 3, 10]]
Index pairs list : [[1, 4, 8], [4, 6, 3], [5, 8, 10]]

Using itertools.zip_longest()

itertools.zip_longest() function is another method to pair elements at the same indices. It allows pairing of elements from lists of unequal lengths by filling missing values with a specified fill value and this method is particularly useful when the input lists have different lengths as it prevents index errors.

from itertools import zip_longest

li = [[1, 4, 5], [4, 6, 8], [8, 3, 10]]

# using zip_longest() to pair index elements
res = [list(x) for x in zip_longest(*li, fillvalue=None)]

print("Index pairs list : " + str(res))

Original list : [[1, 4, 5], [4, 6, 8], [8, 3, 10]]
Index pairs list : [[1, 4, 8], [4, 6, 3], [5, 8, 10]]

Explanation:

• zip_longest(*l, fillvalue=None) pairs elements at corresponding indices and fills missing values with None if any list is shorter.
• The list comprehension [list(x) for x in ...] converts the resulting tuples into lists, creating the final output.

Using a for loop

In this method, we manually loop through the lists and use a temporary list to store the elements that belong to the same index across different lists. For each index, we append the corresponding elements from all lists into the temporary list.

li = [[1, 4, 5], [4, 6, 8], [8, 3, 10]]

# using a for loop to group elements by index
res = []
for i in range(len(l[0])):
    res.append([x[i] for x in li])

print("Index pairs list : " + str(res))

Original list : [[1, 4, 5], [4, 6, 8], [8, 3, 10]]
Index pairs list : [[1, 4, 8], [4, 6, 3], [5, 8, 10]]

Using pandas DataFrame

Working with larger datasets require more advanced manipulation hence we can use the pandas library. In this method we first convert the the lists into a DataFrame and then we can use the transpose() function that allows us to group elements at the same index across lists.

import pandas as pd

li = [[1, 4, 5], [4, 6, 8], [8, 3, 10]]

# using pandas DataFrame to pair index elements
df = pd.DataFrame(li).T
res = df.values.tolist()

print("Index pairs list : " + str(res))

Original list : [[1, 4, 5], [4, 6, 8], [8, 3, 10]]
Index pairs list : [[1, 4, 8], [4, 6, 3], [5, 8, 10]]

Explanation:

• pd.DataFrame(l) converts the list of lists into a DataFrame and .T transposes the DataFrame so that each row corresponds to the elements at the same index across all lists.
• .values.tolist() converts the transposed DataFrame into a list of lists containing the grouped elements.