# group-by

Organizes the rows returned from a query into groups. Within each group, you can apply an aggregate function, such as `count()` or `sum()` to get the number of items or sum, respectively.

## Syntax

`group-by` takes this syntax.

```nolang
group data_stream by fields;
```

| Parameter     | Description                      |
| ------------- | -------------------------------- |
| *data_stream* | Data input to group.             |
| *fields*      | Fields by which data is grouped. |

## Group-by One Field

In this example, the query counts the number of rows for each `Category` field and groups the counts by category.

```nolang
q = load "Superstore";
q = group q by 'Category';
q = foreach q generate 'Category' as 'Category', count() as 'count';
q = limit q 2000;
```

| Category        | Count of Rows |
| --------------- | ------------- |
| Furniture       | 2,121         |
| Office Supplies | 6,026         |
| Technology      | 1,847         |

:::note
`cogroup` and `group-by` are interchangeable. For clarity, we use `group-by` for statements that involve one data stream and `cogroup` for statements that involve two or more data streams.
:::

## Group-by with Null Values

To return grouped null values in your queries, you must select the preference to include null values in Setup. Otherwise, queries ignore null values.

1. In Setup, enter `Analytics` in the Quick Find box.
2. Select **Settings** from the list of Analytics options.
3. In **Settings**, click the checkbox for **Include null values in Analytics queries**.

![Null handling preference in Setup](https://a.sfdcstatic.com/developer-website/sfdocs/analytics/media/bi_dev_guide_saql/bi_saql_null_handling.png)

Here’s an example of a query that returns null values. It orders the results by the `Sub_Category` field and specifies that the results display in ascending order, with nulls first.

```nolang
q = load "Superstore";
q = group q by 'Sub_Category';
q = foreach q generate 'Sub_Category' as 'Sub_Category', count() as 'count';
q = order q by 'Sub_Category' asc nulls first;
q = limit q 2000;
```

| Sub-Category | Count of Rows |
| ------------ | ------------- |
| -            | 4             |
| Accessories  | 775           |
| Appliances   | 466           |
| Art          | 796           |
| Binders      | 1,523         |
| Bookcases    | 228           |
| Chairs       | 617           |
| Copiers      | 68            |
| Envelopes    | 254           |
| Fasteners    | 217           |
| Furnishings  | 957           |
| Labels       | 364           |
| Machines     | 115           |
| Paper        | 1,370         |
| Phones       | 889           |
| Storage      | 846           |
| Supplies     | 190           |
| Tables       | 319           |

## Group-by all

In this example, the query counts all of the rows and returns the number of different industries that you have opportunities with.

```nolang
q = load "DTC_Opportunity_SAMPLE";
q = group q by all;
q = foreach q generate unique('Industry') as 'unique_Industry';
```

| # | Unique of Industry |
| - | ------------------ |
| 1 | 20                 |

**See Also**

- [Aggregate Functions](/docs/analytics/bi-dev-guide-saql/guide/bi-saql-functions-aggregate.md)
- [Null Operators](/docs/analytics/bi-dev-guide-saql/guide/bi-saql-operators-null.md)
- [cogroup](/docs/analytics/bi-dev-guide-saql/guide/bi-saql-statement-cogroup.md)
- [Use Group and Filter Pre-projection](/docs/analytics/bi-dev-guide-saql/guide/bi-saql-performance-group-filter.md)