insert(arr, obj, values, axis)
This docstring was copied from numpy.insert.
Some inconsistencies with the Dask version may exist.
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`.
Input array.
Object that defines the index or indices before which values
is inserted.
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 to insert into :None:None:`arr`. If the type of values
is different from that of :None:None:`arr`, values
is converted to the type of :None:None:`arr`. values
should be shaped so that arr[...,obj,...] = values
is legal.
Axis along which to insert values
. If :None:None:`axis` is None then :None:None:`arr` is flattened first.
A copy of :None:None:`arr` with 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.
append
Append elements at the end of an array.
concatenate
Join a sequence of arrays along an existing axis.
delete
Delete elements from an array.
>>> a = np.array([[1, 1], [2, 2], [3, 3]]) # doctest: +SKIPThis example is valid syntax, but we were not able to check execution
... a # doctest: +SKIP array([[1, 1], [2, 2], [3, 3]])
>>> np.insert(a, 1, 5) # doctest: +SKIP array([1, 5, 1, ..., 2, 3, 3])This example is valid syntax, but we were not able to check execution
>>> np.insert(a, 1, 5, axis=1) # doctest: +SKIP array([[1, 5, 1], [2, 5, 2], [3, 5, 3]])
Difference between sequence and scalars:
This example is valid syntax, but we were not able to check execution>>> np.insert(a, [1], [[1],[2],[3]], axis=1) # doctest: +SKIP array([[1, 1, 1], [2, 2, 2], [3, 3, 3]])This example is valid syntax, but we were not able to check execution
>>> np.array_equal(np.insert(a, 1, [1, 2, 3], axis=1), # doctest: +SKIPThis example is valid syntax, but we were not able to check execution
... np.insert(a, [1], [[1],[2],[3]], axis=1)) True
>>> b = a.flatten() # doctest: +SKIPThis example is valid syntax, but we were not able to check execution
... b # doctest: +SKIP array([1, 1, 2, 2, 3, 3])
>>> np.insert(b, [2, 2], [5, 6]) # doctest: +SKIP array([1, 1, 5, ..., 2, 3, 3])This example is valid syntax, but we were not able to check execution
>>> np.insert(b, slice(2, 4), [5, 6]) # doctest: +SKIP array([1, 1, 5, ..., 2, 3, 3])This example is valid syntax, but we were not able to check execution
>>> np.insert(b, [2, 2], [7.13, False]) # type casting # doctest: +SKIP array([1, 1, 7, ..., 2, 3, 3])This example is valid syntax, but we were not able to check execution
>>> x = np.arange(8).reshape(2, 4) # doctest: +SKIPSee :
... idx = (1, 3) # doctest: +SKIP
... np.insert(x, idx, 999, axis=1) # doctest: +SKIP array([[ 0, 999, 1, 2, 999, 3], [ 4, 999, 5, 6, 999, 7]])
The following pages refer to to this document either explicitly or contain code examples using this.
dask.array.routines.delete
dask.array.routines.insert
dask.array.routines.append
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