NumPy's fromiter() function is a handy tool for creating a NumPy array from an iterable object. This iterable can be any Python object that provides elements one at a time. The function is especially useful when you need to convert data from a custom data source, like a file or generator, into a NumPy array for further analysis.

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()':

import numpy as np

my_iterable=[1,2,3,4,5,6]

my_array=np.fromiter(my_iterable,dtype=int)

print(my_array)

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.

import numpy as geek

iterable = (x * x*x for x in range(4))

gfg = geek.fromiter(iterable, int)

print (gfg)

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.

# Python program explaining
# numpy.fromiter() function 
           
# importing numpy as geek 
import numpy as geek

iterable = (x * x for x in range(6))

gfg = geek.fromiter(iterable, float)

print (gfg)

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.

# Python program explaining numpy.fromiter() function 
           
import numpy as np

unicode=[71,101,101,107]

array=np.fromiter(unicode,dtype='U')

print(array)

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:

# importing the module
import numpy as np

# creating the string
a = "python"

# creating 1-d array
b = np.fromiter(a, dtype='U2')
print(b)

Output:

['p' 'y' 't' 'h' 'o' 'n']