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NumPy | remainder method

schedule Aug 11, 2023
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Numpy's `remainder(~)` method computes the remainder element-wise given two arrays. Numpy's `mod(~)` method is equivalent to this method.

WARNING

Opt to use the `%` operator instead

If you don't need the 3rd and 4th parameters of this method, simply multiply two arrays using the `%` operator - you'll enjoy a performance boost.

Parameters

1. `x1` | `array_like`

The values that will be dividend.

2. `x2` | `array_like`

The values to divide by.

3. `out` | `Numpy array` | `optional`

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

4. `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 behaviour is slightly different - the original value will be kept intact.

Return value

A scalar is returned if `x1` and `x2` are scalars, otherwise a Numpy array is returned.

Examples

A common divisor

``` x = [5, 8]np.remainder(x, 2) array([1, 0]) ```

Element-wise division

``` x = [5, 8]np.remainder(x, [2,3]) array([1, 2]) ```

Here, we're simply performing `5%2=1` and `8%3=2`.

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