# Formula Columns

> Perform calculations and data transformations using EraQL expressions - similar to spreadsheet formulas but built for your datasets.

Source: https://cotera.co/docs/guides/columns/expression

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Formula columns let you perform calculations and data transformations on your dataset - similar to formulas in a spreadsheet, but designed for large-scale data processing. They use EraQL, Cotera's functional query language, to compute new values from your existing data without requiring AI.

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## When to Use Formula Columns

Formula columns are ideal when you need deterministic, rule-based transformations:

* **Calculations**: Compute totals, percentages, differences, or aggregations
* **Data formatting**: Standardize text, extract substrings, or combine fields
* **Conditional logic**: Apply if/then rules based on your data
* **Date operations**: Calculate durations, extract date parts, or format timestamps
* **Type conversions**: Convert between strings, numbers, and other data types

For tasks requiring judgment, interpretation, or natural language understanding, use [LLM columns](https://cotera.co/docs/guides/how-to-create-an-llm-column.md) instead.

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## Quick Examples

Here are some common formula patterns:

**Combine first and last name:**

```
concat("first_name", ' ', "last_name")
```

**Calculate a percentage:**

```
div("completed_tasks", "total_tasks") |> mul(100)
```

**Extract the month from a date:**

```
date_part("created_at", 'month')
```

**Conditional value:**

```
if("amount" > 1000, {then: 'high_value', else: 'standard'})
```

**Clean and standardize text:**

```
lower("email") |> replace(' ', '')
```

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## EraQL: The Formula Language

Formula columns are powered by EraQL, a functional query language with a rich set of built-in functions for:

* **Math**: `add`, `sub`, `mul`, `div`, `round`, `abs`, `floor`, `ceil`
* **Strings**: `concat`, `lower`, `upper`, `replace`, `substring`, `split_part`
* **Dates**: `date_add`, `date_diff`, `date_trunc`, `date_part`, `now`
* **Logic**: `if`, `and`, `or`, `not`, `coalesce`, `is_null`
* **Comparisons**: `eq`, `gt`, `lt`, `gte`, `lte`, `one_of`

For the complete syntax and all available functions, see the **[EraQL Language Reference](https://cotera.co/docs/reference/eraql/language-reference.md)**.

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## Creating a Formula Column

1. Navigate to your dataset and open the column editor
2. Select **Formula** as the column type
3. Write your EraQL expression
4. Use the preview feature to test on sample data
5. Publish when ready

Formula columns execute instantly and deterministically - the same input always produces the same output, making them reliable for business-critical calculations.