This is documentation for an old release of NumPy (version 1.19). 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

arrarray_like

Input array.

objslice, int or array of ints

Indicate indices of sub-arrays to remove along the specified axis.

Changed in version 1.19.0: Boolean indices are now treated as a mask of elements to remove, rather than being cast to the integers 0 and 1.

axisint, optional

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

Returns

outndarray

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:

>>>

>>> arr = np.arange(12) + 1
>>> 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])