Basic NumPy array replacement

Question

I have a rather basic question about the NumPy module in Python 2, particularly the version on trinket.io. I do not see how to replace values in a multidimensional array several layers in, regardless of the method. Here is an example:

a = numpy.array([1,2,3])
a[0] = 0

print a

a = numpy.array([[1,2,3],[1,2,3]])
a[0][0] = a[1][0] = 0

print a

Result:

array([0, 2, 3], '<class 'int'>')
array([[1, 2, 3], [1, 2, 3]], '<class 'int'>')

I need the ability to change individual values, my specific code being:

a = numpy.empty(shape = (8,8,2),dtype = str)

for row in range(a.shape[0]):
  for column in range(a.shape[1]):
    a[row][column][1] = 'a'

Thank you for your time and any help provided.

Your code works for me and prints the expected results [0 2 3] and [[0 2 3], [0 2 3]]. What version of Python and numpy are you using? — Hannes Ovrén
– Hannes Ovrén, Commented May 4, 2016 at 14:09
An unspecified version of python 2 and numpy on trinket.io, trinket.io/library/trinkets/create?lang=python — InGaN
– InGaN, Commented May 4, 2016 at 15:14

user3408085 · Accepted Answer · 2016-05-04 14:15:55Z

1

To change individual values you can simply do something like:

a[1,2] = 'b'

If you want to change all the array, you can do:

a[:,:] = 'c'

Use commas (array[a,b]) instead of (array[a][b])

answered May 4, 2016 at 14:15

user3408085

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InGaN Over a year ago

Unfortunately this results in a ValueError being raised if I just try to access the value with your method, ex: import numpy a = numpy.empty(shape = (8,8,2),dtype = str) print a[0,0,0] Result: ValueError: Tuple must contain values for all dimensions on line 5 in main.py

Peter · Accepted Answer · 2016-05-04 15:06:15Z

0

With numpy version 1.11.0, I get

[[0 2 3]
 [0 2 3]]

When I run your code. I guess your numpy version is newer and better.

As user3408085 said, the correct thing is to go a[0,0] = 0 to change one element or a[:,0]=0 if your actually want to zero the entire first column.

The reason a[0][0]=0 does not modify a (at least in your version of numpy) is that a[0] is a new array. If break down your command a[0][0]=0 into 2 lines:

b=a[0]
b[0]=0

Then the fact that this modifies a is counterintuitive.

edited May 4, 2016 at 15:06

answered May 4, 2016 at 14:47

Peter

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1 Comment

Hannes Ovrén Over a year ago

a[0] is a view of the first row of matrix a. It is not copied, and I don't think this has been the case for any numpy version. You can check this easily with c = a[0]; c[1] = 99; print a

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