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# NumPy | fromiter method

schedule Aug 10, 2023
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Numpy's `fromiter(~)` method constructs a Numpy array from an iterable object (e.g. lists and strings).

# Parameters

1. `iterable` | `iterable object`

An iterable object such as lists and strings.

2. `dtype` | `string` or `type`

The data type of the resulting array.

3. `count`link | `int` | `optional`

The number of values to read from `iterable`. By default, `count=-1`, which means that all values are read.

NOTE

Specify `count` to improve performance

By specifying count, Numpy can create an array of fixed size upfront without having to dynamically resize the array during iteration.

A Numpy array.

# Examples

## Basic usage

To create a Numpy array from a Python list:

``` x = [3,4,5]np.fromiter(x, dtype=int) array([3, 4, 5]) ```

To create a Numpy array from a byte string:

``` x = "Cats"np.fromiter(x, dtype="S1") array([b'C', b'a', b't', b's'], dtype='|S1') ```

Here, the data-type `S1` just means a string of length `1`.

## Specifying count

To only consider the first 2 items:

``` x = [3,4,5]np.fromiter(x, dtype=int, count=2) array([3, 4]) ```
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