numpy.split(ary, indices_or_sections, axis=0)
Split an array into multiple sub-arrays as views into ary.
Parameters:aryndarrayArray to be divided into sub-arrays.
indices_or_sectionsint or 1-D arrayIf indices_or_sections is an integer, N, the array will be divided into N equal arrays along axis. If such a split is not possible, an error is raised.
If indices_or_sections is a 1-D array of sorted integers, the entries indicate where along 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 axis, an empty sub-array is returned correspondingly.
axisint, optionalThe axis along which to split, default is 0.
Returns:sub-arrayslist of ndarraysA list of sub-arrays as views into ary.
Raises:ValueErrorIf indices_or_sections is given as an integer, but a split does not result in equal division.
See also
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.
Split array into multiple sub-arrays horizontally (column-wise).
Split array into multiple sub-arrays vertically (row wise).
Split array into multiple sub-arrays along the 3rd axis (depth).
Join a sequence of arrays along an existing axis.
Join a sequence of arrays along a new axis.
Stack arrays in sequence horizontally (column wise).
Stack arrays in sequence vertically (row wise).
Stack arrays in sequence depth wise (along third dimension).
Examples
>>> importnumpyasnp>>> 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)>>> np.split(x,[3,5,6,10])[array([0., 1., 2.]), array([3., 4.]), array([5.]), array([6., 7.]), array([], dtype=float64)]