Document

insert(arr, obj, values, axis=None)

Notes

Note that for higher dimensional inserts :None:None:`obj=0` behaves very different from :None:None:`obj=[0]` just like :None:None:`arr[:,0,:] = values` is different from :None:None:`arr[:,[0],:] = values`.

Parameters

arr : array_like

Input array.

obj : int, slice or sequence of ints

Object that defines the index or indices before which :None:None:`values` is inserted.

versionadded

Support for multiple insertions when :None:None:`obj` is a single scalar or a sequence with one element (similar to calling insert multiple times).

values : array_like

Values to insert into :None:None:`arr`. If the type of :None:None:`values` is different from that of :None:None:`arr`, :None:None:`values` is converted to the type of :None:None:`arr`. :None:None:`values` should be shaped so that arr[...,obj,...] = values is legal.

axis : int, optional

Axis along which to insert :None:None:`values`. If :None:None:`axis` is None then :None:None:`arr` is flattened first.

Returns

out : ndarray: A copy of :None:None:`arr` with :None:None:`values` inserted. Note that insert does not occur in-place: a new array is returned. If :None:None:`axis` is None, :None:None:`out` is a flattened array.

Insert values along the given axis before the given indices.

Examples

>>> a = np.array([[1, 1], [2, 2], [3, 3]])
... a
array([[1, 1],
       [2, 2],
       [3, 3]])

>>> np.insert(a, 1, 5)
array([1, 5, 1, ..., 2, 3, 3])

>>> np.insert(a, 1, 5, axis=1)
array([[1, 5, 1],
       [2, 5, 2],
       [3, 5, 3]])

Difference between sequence and scalars:

>>> np.insert(a, [1], [[1],[2],[3]], axis=1)
array([[1, 1, 1],
       [2, 2, 2],
       [3, 3, 3]])

>>> np.array_equal(np.insert(a, 1, [1, 2, 3], axis=1),
...                np.insert(a, [1], [[1],[2],[3]], axis=1))
True

>>> b = a.flatten()
... b
array([1, 1, 2, 2, 3, 3])

>>> np.insert(b, [2, 2], [5, 6])
array([1, 1, 5, ..., 2, 3, 3])

>>> np.insert(b, slice(2, 4), [5, 6])
array([1, 1, 5, ..., 2, 3, 3])

>>> np.insert(b, [2, 2], [7.13, False]) # type casting
array([1, 1, 7, ..., 2, 3, 3])

>>> x = np.arange(8).reshape(2, 4)
... idx = (1, 3)
... np.insert(x, idx, 999, axis=1)
array([[  0, 999,   1,   2, 999,   3],
       [  4, 999,   5,   6, 999,   7]])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.linalg._decomp_update.qr_insert dask.array.routines.insert numpy.append numpy.delete numpy.insert

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