0

I have some numpy arrays with None in the first position.

a = [None, 1, 2, 3, 4, 5]
b = [None, 4, 3, 2, 1, 5]

I want it to become:

[1, 2, 3, 4, 5]
[4, 3, 2, 1, 5]

EDIT: I know I can do:

a = [a is not None]

But In my case I want to specifically remove a[0]

tried:

a = np.delete(a, 0)

got:

AttributeError: int' object has no attribute 'delete'
bakun
  • 448
  • 1
  • 9
  • 17
  • Does this answer your question? [How to remove all rows in a numpy.ndarray that contain non-numeric values](https://stackoverflow.com/questions/11453141/how-to-remove-all-rows-in-a-numpy-ndarray-that-contain-non-numeric-values) – Mateo Torres Nov 17 '20 at 18:35
  • `arr[:, 1:]` will select all but the first column. With `None` the array will be object dtype. Without it it could be converted to numeric dtype, as with `arr[:, 1:].astype(int)`. – hpaulj Nov 17 '20 at 18:36
  • Does this answer your question? [efficient way of removing None's from numpy array](https://stackoverflow.com/questions/25254929/efficient-way-of-removing-nones-from-numpy-array) – Rivers Nov 17 '20 at 18:36
  • It partly does, but this methods search the None's (O(n)). In my case, I know that it is in array[0]. There is not there a better way? – bakun Nov 17 '20 at 18:45
  • Does this answer your question? [How to remove specific elements in a numpy array](https://stackoverflow.com/questions/10996140/how-to-remove-specific-elements-in-a-numpy-array) – Mayank Porwal Nov 17 '20 at 18:52
  • AttributeError: int' object has no attribute 'delete' – bakun Nov 17 '20 at 18:58
  • 1
    You have messed up the `np` variable. It no longer is the imported module. Start over! – hpaulj Nov 17 '20 at 19:21
  • as @hpaulj mentioned, your `np` now is an integer, do `print(np)` to see. Standard numpy import should give you `module 'numpy'...` – Quang Hoang Nov 17 '20 at 19:45

2 Answers2

2

a is a list:

In [61]: a = [None, 1,2,3,4]
In [62]: a
Out[62]: [None, 1, 2, 3, 4]
In [63]: a[1:]               # standard list slicing
Out[63]: [1, 2, 3, 4]

If we have an array, we can do the same slicing:

In [64]: A = np.array(a)
In [65]: A
Out[65]: array([None, 1, 2, 3, 4], dtype=object)
In [66]: A[1:]
Out[66]: array([1, 2, 3, 4], dtype=object)
In [67]: A[1:].astype(int)
Out[67]: array([1, 2, 3, 4])

With None the array is object dtype, similar to a list.

With the list, we can also us del (and remove any selected item):

In [68]: a
Out[68]: [None, 1, 2, 3, 4]
In [69]: del a[0]
In [70]: a
Out[70]: [1, 2, 3, 4]

np.delete does something similar for an array, though it isn't as efficient:

In [72]: np.delete(A, 0)
Out[72]: array([1, 2, 3, 4], dtype=object)

If np.delete doesn't work for you, it's because you've messed up np.

hpaulj
  • 221,503
  • 14
  • 230
  • 353
  • Slicing solved it! As for np.delete, it worked when I tested it on some random array, but for some reason it is not working in my program's array.. anyway ty! – bakun Nov 17 '20 at 20:14
0

Numpy just have a beautiful method. Use .delete()

Example:

n = [None, 1, 2, 3, 4, 5]
n = np.delete(n, 0)

EDIT : np stands for numpy. Use: import numpy as np

sushanth
  • 8,275
  • 3
  • 17
  • 28
HolySpeeddo
  • 65
  • 6