This is documentation for an old release of NumPy (version 1.13). Read this page Search for this page in the documentation of the latest stable release (version 2.2).

numpy.delete

numpy.delete(arr, obj, axis=None)

Return a new array with sub-arrays along an axis deleted. For a one dimensional array, this returns those entries not returned by arr[obj].

Parameters:

arr : array_like

Input array.

obj : slice, int or array of ints

Indicate which sub-arrays to remove.

axis : int, optional

The axis along which to delete the subarray defined by obj. If axis is None, obj is applied to the flattened array.

Returns:

out : ndarray

A copy of arr with the elements specified by obj removed. Note that delete does not occur in-place. If axis is None, out is a flattened array.

See also

insert

Insert elements into an array.

append

Append elements at the end of an array.

Notes

Often it is preferable to use a boolean mask. For example:

>>> mask = np.ones(len(arr), dtype=bool)
>>> mask[[0,2,4]] = False
>>> result = arr[mask,...]

Is equivalent to np.delete(arr, [0,2,4], axis=0), but allows further use of mask.

Examples

>>> arr = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])
>>> arr
array([[ 1,  2,  3,  4],
       [ 5,  6,  7,  8],
       [ 9, 10, 11, 12]])
>>> np.delete(arr, 1, 0)
array([[ 1,  2,  3,  4],
       [ 9, 10, 11, 12]])

>>> np.delete(arr, np.s_[::2], 1)
array([[ 2,  4],
       [ 6,  8],
       [10, 12]])
>>> np.delete(arr, [1,3,5], None)
array([ 1,  3,  5,  7,  8,  9, 10, 11, 12])