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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)  ``

Parameters:

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(x)

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

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

## Summary

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.

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