I want to delete all instances of a value in a numpy array which is shaped in rows.

a = array([5,1,2,4,9,2]).reshape(-1, 1)
print("before delete", a)
a = np.delete(a, np.where(a == 2))
print("after delete", a)

The output is

before delete [[5]
 [1]
 [2]
 [4]
 [9]
 [2]]
after delete [1 4 9]

I don't know why 5 is deleted. I expect to see

[[5]
 [1]
 [4]
 [9]]

How can I fix that?

CodePudding user response：

np.where in this case returns 2 arrays. The first one is the indexes of the values that are equal to 2, but the second is not needed. You need to grab the first one:

a = np.delete(a, np.where(a == 2)[0])

Output:

>>> a
array([5, 1, 4, 9])