applying .astype() for specific indices doesn’t work

I want to change first column to int in dnarray

print(gcp)

[[ 1. 6.218 2.974 0. ] [ 2. 32.881 8.66 0. ] [ 3.
38.94 35.843 0. ] [ 4. 8.52 35.679 0. ] [ 5. 52.902 49.538 0. ]]

print(gcp.dtype)

float64

gcp[:,0] = (gcp[:,0]).astype(int)
print(((gcp[:,0]).astype(int)).dtype)

int32

print(gcp.dtype)

float64

I tried to use deepcopy, but no success. Any help will be good, I didn’t find any similar questions.

Answer

To have just the index of the row(+1) as element of the array seems redundant to me, maybe you don’t need the first row at all. Otherwise the best option to me is to use two arrays:

gcp0 = gcp[:, 0].astype(int)
gcp = gcp[:, 1:]

Another possibility is to define separate named fields with respective dtypes for the separate columns, which brings you maybe closer to pandas, which is another option you have.

gcp = np.array([(1., 6.218,  2.974,  0.),
                (2., 32.881, 8.66,   0.),
                (3., 38.94,  35.843, 0.),
                (4., 8.52,   35.679, 0.),
                (5., 52.902, 49.538, 0.)],
                dtype={'names':   ['index', 'a0', 'a1', 'a2'],
                       'formats': [int, float, float, float]})

print(gcp['index'])
# [1 2 3 4 5]