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# NumPy | absolute method

schedule Aug 10, 2023
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Numpy's `np.absolute(~)` method returns a Numpy array with the absolute value applied to each of its value.

NOTE

`np.abs(~)` is shorthand for `np.absolute(~)`

# Parameter

1. `x` | `array-like`

The input array.

2. `out` | `Numpy array` | `optional`

Instead of creating a new array, you can place the computed mean into the array specified by `out`.

3. `where` | `array` of `boolean` | `optional`

Values that are flagged as False will be ignored, that is, their original value will be uninitialized. If you specified the `out` parameter, the behavior is slightly different - the original value will be kept intact.

# Return value

A Numpy array with the absolute value applied to each of its value.

# Examples

To return a Numpy array with the absolute values of array `x`:

``` x = np.array([-1, 2, 3, -4])np.absolute(x) array([1, 2, 3, 4]) ```

Note that the source Numpy array is left intact, that is, `x` in this example would still have negative values.

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