How to access a column in a list of lists in python
Question:
I have a 2D array in python modeled by a list of lists and I want to extract the column. I made a quick research and I found a way that uses numpy arrays. The problem is that I do not want to use numpy so I don’t want to convert my list of lists into a numpy array and then use [:,1] syntax. I tried using it on a normal list of lists but it shows an error so it’s not possible. I am asking for a similar thing for list of lists without having to go through each element (In numpy arrays, it’s faster to access a column by using [:,1] syntax than iterating over the elements of the array).
I found this link but again it suggests iterating over elements without a shortcut.
Answers:
List comprehensions are your friend when working with lists of lists:
In [111]: alist
Out[111]:
[[0, 1, 2, 3, 4, 5],
[6, 7, 8, 9, 10, 11],
[12, 13, 14, 15, 16, 17],
[18, 19, 20, 21, 22, 23]]
In [112]: [row[1] for row in alist]
Out[112]: [1, 7, 13, 19]
There’s also a handy ‘idiom’ for transposing a nested list, turning ‘columns’ into ‘rows’:
In [113]: tlist = list(zip(*alist))
In [114]: tlist
Out[114]:
[(0, 6, 12, 18),
(1, 7, 13, 19),
(2, 8, 14, 20),
(3, 9, 15, 21),
(4, 10, 16, 22),
(5, 11, 17, 23)]
In [115]: tlist[1]
Out[115]: (1, 7, 13, 19)
If you’re interested in a more functional approach, you can also use itemgetter from the standard operator library to fetch items in specific position(s) in each sub-list of a nested list.
from operator import itemgetter
mylist = [[0,1], [2,3], [4,5]]
second_column_vals = list(map(itemgetter(1), mylist)) # [1, 3, 5]
first_and_third_column_vals = list(map(itemgetter(0, 2), mylist))
I have a 2D array in python modeled by a list of lists and I want to extract the column. I made a quick research and I found a way that uses numpy arrays. The problem is that I do not want to use numpy so I don’t want to convert my list of lists into a numpy array and then use [:,1] syntax. I tried using it on a normal list of lists but it shows an error so it’s not possible. I am asking for a similar thing for list of lists without having to go through each element (In numpy arrays, it’s faster to access a column by using [:,1] syntax than iterating over the elements of the array).
I found this link but again it suggests iterating over elements without a shortcut.
List comprehensions are your friend when working with lists of lists:
In [111]: alist
Out[111]:
[[0, 1, 2, 3, 4, 5],
[6, 7, 8, 9, 10, 11],
[12, 13, 14, 15, 16, 17],
[18, 19, 20, 21, 22, 23]]
In [112]: [row[1] for row in alist]
Out[112]: [1, 7, 13, 19]
There’s also a handy ‘idiom’ for transposing a nested list, turning ‘columns’ into ‘rows’:
In [113]: tlist = list(zip(*alist))
In [114]: tlist
Out[114]:
[(0, 6, 12, 18),
(1, 7, 13, 19),
(2, 8, 14, 20),
(3, 9, 15, 21),
(4, 10, 16, 22),
(5, 11, 17, 23)]
In [115]: tlist[1]
Out[115]: (1, 7, 13, 19)
If you’re interested in a more functional approach, you can also use itemgetter from the standard operator library to fetch items in specific position(s) in each sub-list of a nested list.
from operator import itemgetter
mylist = [[0,1], [2,3], [4,5]]
second_column_vals = list(map(itemgetter(1), mylist)) # [1, 3, 5]
first_and_third_column_vals = list(map(itemgetter(0, 2), mylist))