---
title: "mean"
description: "Calculates the mean (a.k.a average) for the numbers in the given column of the given dataset or the mean of a series of numbers specified as arguments."
---

# mean

> Calculates the mean (a.k.a average) for the numbers in the given column of the given dataset or the mean of a series of numbers specified as arguments.

**This function is used by Ignition's Expression language.**

## Description
Calculates the mean (a.k.a average) for the numbers in the given column of the given dataset or the mean of a series of numbers specified as arguments. When looking up the mean in a dataset, the column may be specified as an index or as a column name. Any null values in the column are ignored. If there are no rows in the dataset, null is returned.

## Syntax (index)
`mean(dataset, columnIndex)`

### Parameters

| Type | Parameter | Description |
|---|---|---|
| Dataset | `dataset` | The dataset to use. |
| Integer | `columnIndex` | The index of the column to use. Must be a column index of the provided dataset. |

### Returns
**Integer/Float** - The mean of the values in that column.

## Syntax (name)
`mean(dataset, columnName)`

### Parameters

| Type | Parameter | Description |
|---|---|---|
| Dataset | `dataset` | The dataset to use. |
| String | `columnName` | The name of the column to search through. Must match a column name in the provided dataset. |

### Returns
**Integer/Float** - The mean of the values in that column.

## Syntax (value)
`mean(value[, value...])`

### Parameters

| Type | Parameter | Description |
|---|---|---|
| Integer/Float | `value` | A number. Can be as many values as needed. Can be either a float or an integer. |

### Returns
**Integer/Float** - The mean of the values.

## Syntax (sequence)
 The following overload was added in 8.1.8:

`mean(sequence)`

### Parameters

| Type | Parameter | Description |
|---|---|---|
| Sequence | `sequence` | A list, tuple, array, or set of numerical values. |

### Returns
**Integer/Float** - The mean of the values.

## Examples
For example, suppose you had a table with this dataset in it:
 

| ProductCode |Quantity |Weight |
|---|---|---|
| BAN_002 |380 |3.243 |
| BAN_010 |120 |9.928 |
| APL_000 |125 |1.287 |
| FWL_220 |322 |7.889 |

```python title="Code Snippet"
mean({Root Container.Table.data}, "Weight") //... would return 5.58675
```
```python title="Code Snippet"
mean(1,2,3) //... would return 2
```