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# NumPy | frombuffer method

schedule Aug 12, 2023
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Numpy's `frombuffer(~)` method constructs a Numpy array from a buffer.

# Parameters

1. `buffer` | `buffer_like`

An object with a buffer interface.

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

The data type of the resulting array. By default, `dtype=float`.

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

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

4. `offset`link | `int` | `optional`

The integer index from which to start reading the buffer (inclusive). By default, `offset=0`.

A Numpy array.

# Examples

## Basic usage

To create a Numpy array from a byte string:

``` x = b"cats."np.frombuffer(x, dtype="S1") array([b'c', b'a', b't', b's', b'.'], dtype='|S1') ```

A couple of things to note here:

• the `b` is used to encode our string from unicode into bytes.

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

## Specifying count

To only consider the first 2 items:

``` x = b"cats."np.frombuffer(x, dtype="S1", count=2) array([b'c', b'a'], dtype='|S1') ```

## Specifying offset

To start reading from a specific index:

``` np.frombuffer(x, dtype="S1", offset=1) array([b'a', b't', b's', b'.'], dtype='|S1') ```
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