Deleting multiple elements at once from a numpy 2d array

your index should be for flat array else it only works to remove a row or column.

Here is how you can convert index and use it

arr = np.array([
    [0.15393912, 0.08129568, 0.34958515, 0.21266128, 0.92372852],
    [0.42450441, 0.1027468 , 0.13050591, 0.60279229, 0.41168151],
    [0.06330729, 0.60704682, 0.5340644 , 0.47580567, 0.42528617],
    [0.27122323, 0.42713967, 0.94541073, 0.21462462, 0.07293321]
])

idxs = [(0,1), (1,3), (2, 1), (3,4)]

idxs = [i*arr.shape[1]+j for i, j in idxs]

np.delete(arr, idxs).reshape(4,4)

for reshaping you should remove the items such that there will be equal number of items and rows and columns after deletion

Numpy doesn't know that you are removing exactly one element per row when you give it arbitrary indices like that. Since you do know that, I would suggest using a mask to shrink the array. Masking has the same problem: it doesn't assume anything about the shape of the result (because it can't in general), and returns a raveled array. You can reinstate the shape you want quite easily though. In fact, I would suggest removing the first element of each index entirely, since you have one per row:

 def remove_indices(a, idx):
     if len(idx) != len(idx): raise ValueError('Wrong number of indices')
     mask = np.ones(a.size, dtype=np.bool_)
     mask[np.arange(len(idx)), idx] = False
     return a[mask].reshape(a.shape[0], a.shape[1] - 1)

Here is a method using np.where

import numpy as np
import operator as op

a = np.arange(20.0).reshape(4,5)
idxs = [(0,1), (1,3), (2, 1), (3,4)]

m,n = a.shape

# extract column indices
# there are simpler ways but this is fast
columns = np.fromiter(map(op.itemgetter(1),idxs),int,m)

# build decimated array
result = np.where(columns[...,None]>np.arange(n-1),a[...,:-1],a[...,1:])

result
# array([[ 0.,  2.,  3.,  4.],
#        [ 5.,  6.,  7.,  9.],
#        [10., 12., 13., 14.],
#        [15., 16., 17., 18.]])

As the documentation says

Return a new array with sub-arrays along an axis deleted.

np.delete deletes a row or a column based on the value of the parameter axis.

Secondly np.delete expects int or array of ints as parameter and not a list of tuples.

you need to specify what the requirement is.

As @divakar suggested look at other answers on Stackoverflow regarding deleting individual items in numpy array.