split(ary, indices_or_sections, axis=0)
Array to be divided into sub-arrays.
If :None:None:`indices_or_sections`
is an integer, N, the array will be divided into N equal arrays along :None:None:`axis`
. If such a split is not possible, an error is raised.
If :None:None:`indices_or_sections`
is a 1-D array of sorted integers, the entries indicate where along :None:None:`axis`
the array is split. For example, [2, 3]
would, for axis=0
, result in
ary[:2]
ary[2:3]
ary[3:]
If an index exceeds the dimension of the array along :None:None:`axis`
, an empty sub-array is returned correspondingly.
The axis along which to split, default is 0.
If :None:None:`indices_or_sections`
is given as an integer, but a split does not result in equal division.
A list of sub-arrays as views into :None:None:`ary`
.
Split an array into multiple sub-arrays as views into :None:None:`ary`
.
array_split
Split an array into multiple sub-arrays of equal or near-equal size. Does not raise an exception if an equal division cannot be made.
concatenate
Join a sequence of arrays along an existing axis.
dsplit
Split array into multiple sub-arrays along the 3rd axis (depth).
dstack
Stack arrays in sequence depth wise (along third dimension).
hsplit
Split array into multiple sub-arrays horizontally (column-wise).
hstack
Stack arrays in sequence horizontally (column wise).
stack
Join a sequence of arrays along a new axis.
vsplit
Split array into multiple sub-arrays vertically (row wise).
vstack
Stack arrays in sequence vertically (row wise).
>>> x = np.arange(9.0)
... np.split(x, 3) [array([0., 1., 2.]), array([3., 4., 5.]), array([6., 7., 8.])]
>>> x = np.arange(8.0)See :
... np.split(x, [3, 5, 6, 10]) [array([0., 1., 2.]), array([3., 4.]), array([5.]), array([6., 7.]), array([], dtype=float64)]
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.ma.extras.hsplit
numpy.hsplit
numpy.stack
numpy.vsplit
numpy.ma.extras.stack
numpy.concatenate
numpy.core._multiarray_umath.concatenate
numpy.char.rsplit
numpy.array_split
numpy.dsplit
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