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NumPy fromiter() function

In this tutorial, we will cover numpy.fromiter() function of Numpy library.

The numpy.fromiter() function is used to create an ndarray by using a python iterable object. This method mainly returns a one-dimensional ndarray object.

Syntax of numpy.fromiter():

Below we have the required syntax to use this function:

numpy.fromiter(iterable, dtype, count)  


Let us discuss the parameters of the above function:

  1. iterable
    This parameter is used to represents an iterable object.

  2. dtype
    This parameter is used to represent the data type of the resultant array items.

  3. count:
    This parameter is used to represent the number of items to read from the buffer in the array.

Note: It is important to specify a count parameter in order to improve performance of this function. Because the count parameter allows the fromiter() function to pre-allocate the output array rather than resizing it on demand.

Returned Value:

This function will return the array created using the iterable object.

Let us now discuss some examples using fromiter() function.

Basic Example:

Below we have the code snippet of the example using this function:

import numpy as np  

a = [0,2,4,9,10,8]  
it = iter(a)  
x = np.fromiter(it, dtype = float)  

print("The output array is :")

print("The type of output array is:")

The output array is :
[ 0. 2. 4. 9. 10. 8.]
The type of output array is:
<class 'numpy.ndarray'>


In this tutorial we covered numpy.fromiter() function in the Numpy library. We also covered its syntax, parameters as well as the value returned by this function along with code example.