numpy.fromiter() function – Python

Last Updated : 25 Mar, 2026

fromiter() function creates a NumPy array from any iterable. It is useful for converting data from sources like generators or files into an array for further processing.

Syntax:

numpy.fromiter(iterable, dtype, count = -1)

Parameters:

iterable: The iterable object providing data for the array.
dtype: [data-type] Data-type of the returned array.
count: [int, optional] Number of items to read.

Returns: [ndarray] The output array.

Numpy.fromiter() function creates a Numpy array from an iterable object. where each element is converted and stored in the array. Here is an example of to use 'numpy.fromiter()':

Output

[1 2 3 4 5 6]

Example 1: Using the numpy.fromiter() function to create a NumPy array from an iterable generated by a generator expression.

Output

[ 0 1 8 27]

Example 2: The NumPy array gfg containing the elements generated by the generator expression. In this case, it's the squares of the numbers from 0 to 5.

Output

[ 0. 1. 4. 9. 16. 25.]

To create a Numpy array from Unicode charcters using 'numpy.froiter()', you can pass an iterable of Unicode strings as input.Each Unicode string can be represented using its corresponding code point.

Output

['G' 'e' 'e' 'k']

In Numpy the 'U2' data type reprsents Unicode strings with a fixed length of 2 characters.The 'U' indicates that the data type in Unicode, and the number '2' specifies the length of each string.

Here's an example of to use 'U2' in numpy:

Output