Transpose list of lists

python

transpose

list-comprehension

functional-programming

byAnton Shumikhin·Sep 2, 2024

To transpose a list of lists in Python, use the zip function combined with the unpacking operator *. This combo groups elements on the same index across all sublists, effectively rotating the matrix. Here's the 'show me the money' code:

transposed = [list(sublist) for sublist in zip(*original)]  # Prepare for liftoff 🚀

Let's consider original = [[1,2],[3,4]]. After transposing, transposed would shape up to [[1, 3], [2, 4]].

Transposing using popular Python versions

In Python 3, the zip function produces an iterator of tuples, which ought to become lists for this to fly right:

transposed = list(map(list, zip(*original)))  # Python 3 says: iterators, give me lists!

In Python 2, map automatically returns a list, sparing you the need for list conversion:

transposed = map(list, zip(*original))  # Python 2 💛 lists

Handling unequal length sublists

If your lists of lists sport uneven lengths (also known as jagged lists), use itertools.zip_longest to transpose them, filling in the blank values with None or another assigned value:

from itertools import zip_longest
transposed = list(map(list, zip_longest(*original, fillvalue=None)))  # 💪 Boldly dealing with unequal lengths

NumPy and a major performance boost

Employ the transpose function in NumPy for maximum efficiency with larger datasets:

import numpy as np
transposed = np.transpose(np.array(original)).tolist()  # NumPy brings out the speedster 🏎️

Python < 3's heritage tactics

For historical Python versions, transpose equal-length sublists using:

transposed = map(None, *original)  # Old but gold.😉

Running on all cylinders with Six

If your code needs to run both on Python 2 and 3:

from six.moves import zip_longest
transposed = list(map(list, zip_longest(*original, fillvalue='-')))  # Six, the peacekeeper of pythons 🕊️

Pythonic slashes using List comprehension

For the poetry lovers who favor a more Pythonic approach with list comprehensions:

transposed = [[row[i] for row in original] for i in range(len(original[0]))]  # Elegantly Pythonic 🎩

Preserve your data integrity

Always double-check that sublists are consistently structure to assure transposition doesn't translate to data misalignment!👀

Casting Python 3 output to list

For Python 3 users, be sure to encase your result in list() to avoid receiving an iterator when all expected was a list.

Don't let the columns feel left out

During transposition, treat each sublist as a column in the final matrix. Particularly Crucial when the columns start to get picky about their data! 😉

Transposition tips and tidbits

Adapting to multifaceted data

Complex datasets with varying subtype? No worries, just give thought to your transpose logic to suit non-uniform sublists.

Optimizing the swap

Peep into the structure of your data and kiss goodbye the most compute-intensive part of transposition with the right method. It's all about time, after all! ⏱️