> ## Documentation Index
> Fetch the complete documentation index at: https://numpyts.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Search & Count

> Functions to find indices, percentiles, quantiles, and count non-zero elements: argmin, argmax, percentile, quantile, count_nonzero.

# Search & Count

Functions that locate elements by position (argmin, argmax), compute order statistics (percentile, quantile), or count elements matching a condition.

***

### argmin

Return the index of the minimum value along an axis.

```typescript theme={null}
function argmin(
  a: ArrayLike,
  axis?: number
): number | NDArray;
```

| Parameter | Type        | Default     | Description                                                                    |
| --------- | ----------- | ----------- | ------------------------------------------------------------------------------ |
| `a`       | `ArrayLike` | --          | Input array.                                                                   |
| `axis`    | `number`    | `undefined` | Axis along which to search. When `undefined`, operates on the flattened array. |

**Returns:** `number` when no axis is specified, `NDArray` of indices when an axis is given.

```typescript theme={null}
import { array, argmin } from 'numpy-ts';

argmin(array([5, 1, 3])); // 1

const a = array([[3, 1], [4, 2]]);
argmin(a, 0); // array([0, 0])  -- row indices of column minima
argmin(a, 1); // array([1, 1])  -- column indices of row minima
```

***

### argmax

Return the index of the maximum value along an axis.

```typescript theme={null}
function argmax(
  a: ArrayLike,
  axis?: number
): number | NDArray;
```

| Parameter | Type        | Default     | Description                                                                    |
| --------- | ----------- | ----------- | ------------------------------------------------------------------------------ |
| `a`       | `ArrayLike` | --          | Input array.                                                                   |
| `axis`    | `number`    | `undefined` | Axis along which to search. When `undefined`, operates on the flattened array. |

**Returns:** `number` when no axis is specified, `NDArray` of indices when an axis is given.

```typescript theme={null}
import { array, argmax } from 'numpy-ts';

argmax(array([5, 1, 3])); // 0

const a = array([[3, 1], [4, 2]]);
argmax(a, 0); // array([1, 1])  -- row indices of column maxima
argmax(a, 1); // array([0, 0])  -- column indices of row maxima
```

***

### percentile

Compute the q-th percentile of the data along the specified axis.

```typescript theme={null}
function percentile(
  a: ArrayLike,
  q: number,
  axis?: number,
  keepdims?: boolean
): number | NDArray;
```

| Parameter  | Type                 | Default     | Description                                                 |
| ---------- | -------------------- | ----------- | ----------------------------------------------------------- |
| `a`        | `ArrayLike`          | --          | Input array.                                                |
| `q`        | `number \| number[]` | --          | Percentile(s) to compute, in the range `[0, 100]`.          |
| `axis`     | `number \| number[]` | `undefined` | Axis or axes along which to compute percentiles.            |
| `keepdims` | `boolean`            | `false`     | If `true`, reduced axes are kept as dimensions with size 1. |

**Returns:** `number` for a single percentile over all axes, `NDArray` when computing multiple percentiles or along specific axes.

```typescript theme={null}
import { array, percentile } from 'numpy-ts';

const a = array([1, 2, 3, 4, 5]);

percentile(a, 50);       // 3
percentile(a, [25, 75]); // array([2, 4])

const b = array([[10, 20], [30, 40]]);
percentile(b, 50, 0);   // array([20, 30])
```

***

### quantile

Compute the q-th quantile of the data along the specified axis.

Equivalent to `percentile` but with `q` in the range `[0, 1]` instead of `[0, 100]`.

```typescript theme={null}
function quantile(
  a: ArrayLike,
  q: number,
  axis?: number,
  keepdims?: boolean
): number | NDArray;
```

| Parameter  | Type                 | Default     | Description                                                 |
| ---------- | -------------------- | ----------- | ----------------------------------------------------------- |
| `a`        | `ArrayLike`          | --          | Input array.                                                |
| `q`        | `number \| number[]` | --          | Quantile(s) to compute, in the range `[0, 1]`.              |
| `axis`     | `number \| number[]` | `undefined` | Axis or axes along which to compute quantiles.              |
| `keepdims` | `boolean`            | `false`     | If `true`, reduced axes are kept as dimensions with size 1. |

**Returns:** `number` for a single quantile over all axes, `NDArray` when computing multiple quantiles or along specific axes.

```typescript theme={null}
import { array, quantile } from 'numpy-ts';

const a = array([1, 2, 3, 4, 5]);

quantile(a, 0.5);          // 3
quantile(a, [0.25, 0.75]); // array([2, 4])

const b = array([[10, 20], [30, 40]]);
quantile(b, 0.5, 0);       // array([20, 30])
```

***

### count\_nonzero

Count the number of non-zero elements in the array.

```typescript theme={null}
function count_nonzero(a: ArrayLike, axis?: number): number | NDArray
```

| Parameter  | Type                 | Default     | Description                                                 |
| ---------- | -------------------- | ----------- | ----------------------------------------------------------- |
| `a`        | `ArrayLike`          | --          | Input array.                                                |
| `axis`     | `number \| number[]` | `undefined` | Axis or axes along which to count non-zero values.          |
| `keepdims` | `boolean`            | `false`     | If `true`, reduced axes are kept as dimensions with size 1. |

**Returns:** `number` when counting over all axes, `NDArray` when counting along specific axes.

```typescript theme={null}
import { array, count_nonzero } from 'numpy-ts';

count_nonzero(array([0, 1, 0, 3, 0])); // 2

const a = array([[0, 1, 0], [2, 0, 3]]);
count_nonzero(a);    // 3
count_nonzero(a, 0); // array([1, 1, 1])
count_nonzero(a, 1); // array([1, 2])
```