How to make a copy of a 2D array in Python? [duplicate]

Answer 1

I think np.tile also might be useful

>>> a = np.array([0, 1, 2])
>>> np.tile(a, 2)
array([0, 1, 2, 0, 1, 2])
>>> np.tile(a, (2, 2))
array([[0, 1, 2, 0, 1, 2],
       [0, 1, 2, 0, 1, 2]])
>>> np.tile(a, (2, 1, 2))
array([[[0, 1, 2, 0, 1, 2]],
       [[0, 1, 2, 0, 1, 2]]])

Answer 2

Try this:

from copy import copy, deepcopy
y = deepcopy(x)

I'm not sure, maybe copy() is sufficient.

Answer 3

In your case(since you use list of lists) you have to use deepcopy, because 'The difference between shallow and deep copying is only relevant for compound objects (objects that contain other objects, like lists or class instances): A shallow copy constructs a new compound object and then (to the extent possible) inserts references into it to the objects found in the original. A deep copy constructs a new compound object and then, recursively, inserts copies into it of the objects found in the original.'

Note that sample below is simply intended to show you an example(don't beat me to much) how deepcopy could be implemented for 1d and 2d arrays:

arr = [[1,2],[3,4]]

deepcopy1d2d = lambda lVals: [x if not isinstance(x, list) else x[:] for x in lVals]

dst = deepcopy1d2d(arr)

dst[1][1]=150
print dst
print arr

Answer 4

For 2D arrays it's possible use map function:

old_array = [[2, 3], [4, 5]]
# python2.*
new_array = map(list, old_array)
# python3.*
new_array = list(map(list, old_array))

Answer 5

Using deepcopy() or copy() is a good solution. For a simple 2D-array case

y = [row[:] for row in x]