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()':
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**3 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.
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.
import numpy as np
unicode = [71, 101, 101, 107]
array = np.fromiter((chr(x) for x in unicode), dtype='U1')
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:
import numpy as np
a = "python"
b = np.fromiter(a, dtype='U2')
print(b)
Output
['p' 'y' 't' 'h' 'o' 'n']
