Use the `GROUP BY` clause to group data by values. `GROUP BY` is an optional clause used to group rows that have the same values for all columns and expressions in the list. To output an aggregation for each group, include an aggregate or selector function in the `SELECT` statement. When `GROUP BY` appears in a query, the `SELECT` list can only use columns that appear in the `GROUP BY` list or in aggregate expressions. > [!Note] > > #### Group by aliases > > - `GROUP BY` can use column aliases that are defined in the `SELECT` clause. > - `GROUP BY` won't use an aliased value if the alias is the same as the > original column name. `GROUP BY` uses the original value of the column, > not the transformed, aliased value. We recommended using column ordinals in > in the `GROUP BY` clause to group by transformed values and maintain the > alias identifier. - [Syntax](#syntax) - [Examples](#examples) ## Syntax ```sql SELECT AGGREGATE_FN(field1), tag1 FROM measurement GROUP BY tag1 ``` ## Examples ### Group data by tag values ```sql SELECT AVG(water_level) AS avg_water_level, location FROM h2o_feet GROUP BY location ``` {{< expand-wrapper >}} {{% expand "View example results" %}} | avg_water_level | location | | ----------------: | ------------ | | 5.359142420303919 | coyote_creek | | 3.530712094245885 | santa_monica | {{% /expand %}} {{< /expand-wrapper >}} ### Group data into 15 minute time intervals by tag ```sql SELECT location, DATE_BIN(INTERVAL '15 minutes', time) AS time, COUNT(water_level) AS count FROM h2o_feet WHERE time >= timestamp '2019-09-17T00:00:00Z' AND time <= timestamp '2019-09-17T01:00:00Z' GROUP BY 1, location ORDER BY location, 1 ``` {{< expand-wrapper >}} {{% expand "View example results" %}} The query uses the `COUNT()` function to count the number of `water_level` points per 15 minute interval. Results are then ordered by location and time. | location | time | count | | :----------- | :------------------- | ----: | | coyote_creek | 2019-09-16T23:45:00Z | 1 | | coyote_creek | 2019-09-17T00:00:00Z | 2 | | coyote_creek | 2019-09-17T00:15:00Z | 3 | | coyote_creek | 2019-09-17T00:30:00Z | 2 | | coyote_creek | 2019-09-17T00:45:00Z | 3 | | santa_monica | 2019-09-16T23:45:00Z | 1 | | santa_monica | 2019-09-17T00:00:00Z | 2 | | santa_monica | 2019-09-17T00:15:00Z | 3 | | santa_monica | 2019-09-17T00:30:00Z | 2 | | santa_monica | 2019-09-17T00:45:00Z | 3 | {{% /expand %}} {{< /expand-wrapper >}}