NumPy Tutorial

Python NumPy Tutorial numpy.empty() in Python numpy.empty_like() in Python numpy.eye() in Python numpy.identity() in Python numpy.ones() in Python numpy.ones_like() in Python numpy.zeros in Python numpy.zeros_like() in Python numpy.full() in Python numpy.full_like() in Python numpy.asarray() in Python numpy.frombuffer() in Python numpy.fromiter() in Python numpy.fromstring () in Python numpy.asanyarray() in Python with Example numpy.ascontiguousarray() in Python with Example Numpy.asmatrix() in Python with Example Numpy.copy() in Python with Example numpy.loadtxt() Python numpy.arrange() in Python numpy.linspace() in Python numpy.logspace() in Python numpy.geomspace() in Python numpy.meshgrid() in Python numpy.diag() in Python numpy.diagflat() in Python numpy.tri() in Python numpy.tril() in Python numpy.copyto() in Python numpy.reshape() in Python numpy.ravel() in Python numpy.ndarray.flat() in Python numpy.ndarray.flatten() in Python numpy.rollaxis() in Python numpy.swapaxes() in Python numpy.ndarray.T in Python numpy.transpose() in Python numpy.atleast_1d() in Python numpy.atleast_2d() in Python numpy.atleast_3d() in Python numpy.broadcast_to() in Python numpy.broadcast_arrays() in Python numpy.expand_dims() in Python numpy.squeeze() in Python numpy.asarray_chkfinite() in Python numpy.asscalar() in Python numpy.concatenate() in Python numpy.stack() in Python numpy.column_stack() in Python numpy.dstack() in Python numpy.hstack() in Python numpy.vstack() in Python numpy.split() in Python numpy.tile() in Python numpy.repeat() in Python numpy.delete() in Python numpy.append() in Python numpy.resize() in Python numpy.trim_zeros() in Python numpy.unique() in Python numpy.flip() in Python NumPy vs SciPy

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Numpy Attributes

numpy.fromiter() in Python

numpy.fromiter() in Python The fromiter() function of Python numpy class creates a ndarray by using an iterable object. It returns a one-dimensional ndarray object. Syntax

numpy.fromiter(iterable, dtype, count=-1)
Parameter The numpy.frombuffer() method consists of three parameters, which are as follows:
  1. Iterable: This parameter represents an iterable object.
  2. dtype: It represents the data type of the resultant array items.
  3. count: This functiondepicts the number of items to read from the buffer in the specified array.
Return This function returns an array created by using the iterable object. Example 1
# Python Programming giving an example for 
# numpy.fromiter() function
importnumpy as numpy
my_list = [0,2,4,6] 
it = iter(my_list) 
n = numpy.fromiter(it, dtype = float) 
print(n) 
print(type(n))
Output
[ 0.  2.  4.  6.]
<class 'numpy.ndarray'>