how to skip 2 data index array on numpy

Question

so I have an 8×6 array, then I want to make the array 4×6.the data such as below:

array([[76, 34, 56, 32, 55, 66],
       [99, 23, 11, 34, 45, 32],
       [87, 98, 87, 23, 12, 77],
       [78, 98, 89, 28, 91, 72],
       [76, 42, 45, 23, 56, 87],
       [81, 22, 34, 42, 81, 23],
       [91, 23, 45, 67, 45, 34],
       [87, 98, 23, 45, 23, 55]])

the data I want such below:

array([[87, 98, 87, 23, 12, 77],
       [78, 98, 89, 28, 91, 72],
       [91, 23, 45, 67, 45, 34],
       [87, 98, 23, 45, 23, 55]])

I’ve try use the slices but it doesn’t work for my case. the code is here:

import numpy as np

data = [
    [76,34,56,32,55,66],
    [99,23,11,34,45,32],
    [87,98,87,23,12,77],
    [78,98,89,28,91,72],
    [76,42,45,23,56,87],
    [81,22,34,42,81,23],
    [91,23,45,67,45,34],
    [87,98,23,45,23,55]
]

data = np.array(data)
data[::2]

Asked By: stack offer

||

Source

Answer 1

Use:

data[np.arange(len(data))%4>1]

Or for a generic method:

N = 2
data[np.arange(len(data))%(2*N) >= N]

Output:

array([[87, 98, 87, 23, 12, 77],
       [78, 98, 89, 28, 91, 72],
       [91, 23, 45, 67, 45, 34],
       [87, 98, 23, 45, 23, 55]])

Answered By: mozway

Answer 2

import numpy as np

data = [
    [76,34,56,32,55,66],
    [99,23,11,34,45,32],
    [87,98,87,23,12,77],
    [78,98,89,28,91,72],
    [76,42,45,23,56,87],
    [81,22,34,42,81,23],
    [91,23,45,67,45,34],
    [87,98,23,45,23,55]
]

data = np.array(data)
import itertools


def filter_mask(data, mask):
    return list(itertools.compress(data, itertools.cycle(mask)))

print(filter_mask(data, mask=[0, 0, 1, 1]))

Answered By: Dhananjay Singh

how to skip 2 data index array on numpy

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