numpy.fromiter#

numpy.fromiter(iter,dtype,count=-1,*,like=None)#

Create a new 1-dimensional array from an iterable object.

Parameters:
iteriterable object

An iterable object providing data for the array.

dtypedata-type

The data-type of the returned array.

Changed in version 1.23:Object and subarray dtypes are now supported (note that the finalresult is not 1-D for a subarray dtype).

countint, optional

The number of items to read fromiterable. The default is -1,which means all data is read.

likearray_like, optional

Reference object to allow the creation of arrays which are notNumPy arrays. If an array-like passed in aslike supportsthe__array_function__ protocol, the result will be definedby it. In this case, it ensures the creation of an array objectcompatible with that passed in via this argument.

New in version 1.20.0.

Returns:
outndarray

The output array.

Notes

Specifycount to improve performance. It allowsfromiter topre-allocate the output array, instead of resizing it on demand.

Examples

>>>importnumpyasnp>>>iterable=(x*xforxinrange(5))>>>np.fromiter(iterable,float)array([  0.,   1.,   4.,   9.,  16.])

A carefully constructed subarray dtype will lead to higher dimensionalresults:

>>>iterable=((x+1,x+2)forxinrange(5))>>>np.fromiter(iterable,dtype=np.dtype((int,2)))array([[1, 2],       [2, 3],       [3, 4],       [4, 5],       [5, 6]])
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