[FIXED] NumPy behavior - manipulating array changes original data?

Issue

I have a small array data that undergoes a reshape and a copy

data = np.array([77, 115, 137, 89, 42, 107, 54, 256])

subset = data[:4].reshape(2,2)

newdata = data[4:].copy()

subset[-1,-1] = 0

newdata[1] = 0

print(data)
print(subset)
print(newdata)

Seems pretty simple. My assumption for this is that I would get the following outputs

data = array([ 77, 115, 137, 89, 42, 107, 54, 256])

subset = array([[ 77, 115],
                [137, 0]])

newdata = array([ 42, 0, 54, 256])

I was correct for subset and newdata, but not data itself, which now outputs

data = np.array([77, 115, 137, 0, 42, 107, 54, 256])

The original data array has been modified from what looks like the reshape and copy and changing the 89 to 0

Any help on why and how these methods do in fact modify the original array is greatly appreciated.

Thanks!

Solution

subset is not a copy but a view of data. Thus any change on subset is a change on data too.

Answered By - Julien