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Function insert

numpy/lib/_function_base_impl.py:5405–5585  ·  view source on GitHub ↗

Insert values along the given axis before the given indices. Parameters ---------- arr : array_like Input array. obj : slice, int, array-like of ints or bools Object that defines the index or indices before which `values` is inserted. .. version

(arr, obj, values, axis=None)

Source from the content-addressed store, hash-verified

5403
5404@array_function_dispatch(_insert_dispatcher)
5405def insert(arr, obj, values, axis=None):
5406 """
5407 Insert values along the given axis before the given indices.
5408
5409 Parameters
5410 ----------
5411 arr : array_like
5412 Input array.
5413 obj : slice, int, array-like of ints or bools
5414 Object that defines the index or indices before which `values` is
5415 inserted.
5416
5417 .. versionchanged:: 2.1.2
5418 Boolean indices are now treated as a mask of elements to insert,
5419 rather than being cast to the integers 0 and 1.
5420
5421 Support for multiple insertions when `obj` is a single scalar or a
5422 sequence with one element (similar to calling insert multiple
5423 times).
5424 values : array_like
5425 Values to insert into `arr`. If the type of `values` is different
5426 from that of `arr`, `values` is converted to the type of `arr`.
5427 `values` should be shaped so that ``arr[...,obj,...] = values``
5428 is legal.
5429 axis : int, optional
5430 Axis along which to insert `values`. If `axis` is None then `arr`
5431 is flattened first.
5432
5433 Returns
5434 -------
5435 out : ndarray
5436 A copy of `arr` with `values` inserted. Note that `insert`
5437 does not occur in-place: a new array is returned. If
5438 `axis` is None, `out` is a flattened array.
5439
5440 See Also
5441 --------
5442 append : Append elements at the end of an array.
5443 concatenate : Join a sequence of arrays along an existing axis.
5444 delete : Delete elements from an array.
5445
5446 Notes
5447 -----
5448 Note that for higher dimensional inserts ``obj=0`` behaves very different
5449 from ``obj=[0]`` just like ``arr[:,0,:] = values`` is different from
5450 ``arr[:,[0],:] = values``. This is because of the difference between basic
5451 and advanced :ref:`indexing <basics.indexing>`.
5452
5453 Examples
5454 --------
5455 >>> import numpy as np
5456 >>> a = np.arange(6).reshape(3, 2)
5457 >>> a
5458 array([[0, 1],
5459 [2, 3],
5460 [4, 5]])
5461 >>> np.insert(a, 1, 6)
5462 array([0, 6, 1, 2, 3, 4, 5])

Callers 3

test_basicMethod · 0.90
test_multidimMethod · 0.90
test_0dMethod · 0.90

Calls 9

onesFunction · 0.90
sliceFunction · 0.85
emptyFunction · 0.85
itemMethod · 0.80
wrapMethod · 0.80
astypeMethod · 0.80
arrayFunction · 0.50
ravelMethod · 0.45
argsortMethod · 0.45

Tested by 3

test_basicMethod · 0.72
test_multidimMethod · 0.72
test_0dMethod · 0.72

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