# `arrayReplaceAll`

## Description

Returns a new array where all instances of a specified value are replaced with a new value.

- The element type must match the array type.
- Supported element types include `string`, `bool`, `number`, `interval`, `timestamp`, `regexp`, and `enum`.

## Syntax

Like many functions in DataPrime, `arrayReplaceAll` supports [two notations](https://coralogix.com/docs/dataprime/language-reference/functions-reference/index.md), **function** and **method** notation. These interchangeable forms allow flexibility in how you structure expressions.

```dataprime
arrayReplaceAll(array: array<T>, value: T, newValue: T): array<T>
```

```dataprime
(array: array<T>).arrayReplaceAll(value: T, newValue: T): array<T>
```

## Arguments

| Name     | Type  | Required | Description                                      |
| -------- | ----- | -------- | ------------------------------------------------ |
| array    | array | **true** | The array to modify                              |
| value    | T     | **true** | The value to replace                             |
| newValue | T     | **true** | The replacement value, must match the array type |

## Example

**Use case: Replace outdated schema values in arrays**

Suppose you have a list of values where some still use an outdated schema. Consider the following inputs:

```json
{
    "values": ["NewVal1", "NewVal2", "NewVal3"]
},
{
    "values": ["OldVal1", "NewVal2", "NewVal3"]
}
```

By replacing all occurrences of `"OldVal1"` with `"NewVal1"`, you ensure data consistency before further processing.

### Example query

```dataprime
create updated_values from arrayReplaceAll(values, 'OldVal1', 'NewVal1')
```

```dataprime
create updated_values from values.arrayReplaceAll('OldVal1', 'NewVal1')
```

### Example output

The result will replace all outdated values:

```json
{
    "values": ["NewVal1", "NewVal2", "NewVal3"]
},
{
    "values": ["NewVal1", "NewVal2", "NewVal3"]
}
```