The closest was this one summing columns.
So I'll do something similar in my question:
Say I've a Python 2D list as below:
my_list = [ [1,2,3,4],
[2,4,5,6] ]
I can get the row totals with a list comprehension:
row_totals = [ sum(x) for x in my_list ]
In one line, how can I sum the entire 2d-array?
27
You can do as easy as
sum(map(sum, my_list))
or alternatively
sum(sum(x) for x in my_list))
and call it a day, if you don't expect more than 2 dimensions. Note that the first solution is most likely not the fastest (as in execution time) solution, due to the usage of map(). Benchmark and compare as necessary.
Finally, if you find yourself using multidimensional arrays, consider using NumPy and its superior array-friendly functions. Here's a short excerpt for your problem:
import numpy as np
my_list = np.array([[1,2,3,4], [2,4,5,6]])
np.sum(my_list)
This would work for any number of dimensions your arrays might have.
map is not inherently slow.
map goes away. Otherwise it allocates an unnecessary list.
Another solution using itertools:
>>> from itertools import chain
>>> my_list = [ [1,2,3,4], [2,4,5,6] ]
>>> sum(chain(*my_list))
27
* for lists/tuples, ** for dictionaries): docs.python.org/3/tutorial/…>>> sum ( [ sum(x) for x in [[1,2,3,4], [2,4,5,6]] ] )
27
>>> from itertools import chain
>>> my_list = [[1,2,3,4], [2,4,5,6]]
>>> sum(chain.from_iterable(my_list))
27
You can use sum to first add the inner lists together and then sum the resulting flattened list:
>>> my_list = [ [1,2,3,4], [2,4,5,6] ]
>>> sum(my_list, [])
[1, 2, 3, 4, 2, 4, 5, 6]
>>> sum(sum(my_list, []))
27
