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# NumPy | count_nonzero method

schedule Aug 10, 2023
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Numpy's `count_nonzero(~)` method counts the number of non-zeros in an array along a given axis.

# Parameters

1. `a` | `array-like`

The array on which to perform the method.

2. `axis`link | `int` or `tuple<int>` | `optional`

The axis along which we count the number of non-zeros. By default, `axis=None`.

# Return value

An `int` or `Numpy array` indicating the number of non-zeros in the input array along the given axis.

# Examples

## Basic usage

``` np.count_nonzero([1,0,2,0,3]) 3 ```

## Counting non-zeros row-wise

To count the number of non-zeros row-wise in a 2D Numpy array, use the following:

``` np.count_nonzero([[1,0,1],[0,1,0]], axis=1) array([2, 1]) ```

We get this result because we have 2 non-zeros in the first row, and 1 non-zero in the second row.

## Counting non-zeros column-wise

To count the number of non-zeros column-wise in a 2D Numpy array, use the following:

``` np.count_nonzero([[1,0,1],[0,1,0]], axis=0) array([1, 1, 1]) ```

We get this result because every column contains exactly 1 non-zero value.

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