numpy.fromiter() function – Python
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()’:
Python3
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.
Python3
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.
Python3
# 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.
Python3
# 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:
Python3
# 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']
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