Introduction

The QUERY function allows the user to make SQL-lite queries using the Google Visualization API Query Language on arrays. This article details the exact specifications of QUERY in Google Sheets. For relevant techniques, see QUERY Smush and QUERY Arithmetic.

Function Syntax

QUERY(data, [query], [headers])

data - The array to perform the query on.
- Each column of data can only hold boolean, numeric (including date/time types), or string values.
- In case there are multiple data types in a single column, the majority data type determines the data type of the column for query purposes. Minority data types are considered null values.
query - The query to perform, expressed as a string. By default, it is set to "select *".
- The query must be submitted as a string. It has a separate syntax, which is explained below.
headers - The number of header rows at the top of the data. If omitted or set to -1, the value is guessed based on the content of data.
- It is currently unclear how QUERY guesses the number of header rows in data. Therefore, it is recommended that you always submit a header argument.
- Header rows are combined by joining with a delimiter " ". See QUERY Smush for the related technique.

Query Syntax

"[select] [where] [group by] [pivot by] [order by] [skipping] [limit] [offset] [label] [format] [options]"

Query syntax is divorced from formula syntax, instead following the Google Visualization API Query Language. Queries are characterized by three important parts.

Language Clauses
- These are the broader elements that define the query.
Data Manipulation Functions
- These expand the capabilities of the query, allowing one to apply aggregation, scalar, and arithmetic functions.
Language Elements
1. These consist of literals, identifiers, and reserved words. They are used throughout the query.

Language Clauses

Language clauses determine how information is gathered and processed.

Clause	Usage
select	Selects which columns to return, and in what order. If omitted, all of the table's columns are returned, in their default order.
where	Returns only rows that match a condition. If omitted, all rows are returned.
group by	Aggregates values across rows.
pivot	Transforms distinct values in columns into new columns.
order by	Sorts rows by values in columns.
limit	Limits the number of returned rows.
offset	Skips a given number of first rows.
label	Sets column labels.
format	Formats the values in certain columns using given formatting patterns.
options	Sets additional options.
Each clause takes different arguments and has vastly different effects; there is no singular construction applicable to each.

Select

select Col1
select 1
select Col1, sum(Col2)

The select clause includes columns, aggregates, and literals in the output. Terms should be comma separated, i.e. select Col1, Col2. Literals are uniformly expanded into vectors to match the number of rows in data. For example, =query(A1:A5, "select 1", ) returns a header (generated by the implied 1()) and five 1s, corresponding to the input rows.

The select clause additionally accepts the "*" term, signifying 'all' or 'everything.' If an aggregate is selected, a group by clause is mandatory.

Where

select Col1 where Col1 is not null
select Col1, Col2 where Col1 <> 0 and Col2 <> 0

The where clause returns only rows that meet certain conditions. They use the same comparison operators as Google Sheets, with the redundant addition of !=, which is equivalent to <>. To compare against null, use is null or is not null.

In addition to these comparators, where uses the and, or, and not keywords in order to combine criteria. Parentheses may be used to specify order.

There are also additional keywords exclusive to the where clause.

Clause	Usage
`contains`	Substring match
`starts with`	Prefix match
`ends with`	Suffix match
`matches`	Regular expression match¹
`like`	Wildcard match²

¹ Regular expressions in QUERY are more extensive than the [[REGEX functions]], constituting a full implementation.
² There are two valid wildcards: % signifies zero or more arbitrary characters, and _ represents exactly one of any character.

Group By

select Col1, sum(Col2) group by Col1

The group by clause is used to aggregate values across rows. A single row is created for each distinct combination of values in the group-by clause. The data is automatically sorted by the grouping columns, unless otherwise specified by an order by clause.

If you use a group by clause, then every column listed in the select clause must either be listed in the group by clause, or be wrapped by an aggregation function.

This clause is mandatory when selecting aggregation functions.

Pivot

select Col1, sum(Col2) group by Col1 pivot Col3

The pivot clause is used to transform distinct values in columns into new columns. This behavior is very similar to pivot tables.

If you use a pivot clause, then every column listed in the select clause must either be listed in the group by clause or be wrapped by an aggregation function. As a result, pivot is very frequently used with group by.

You can pivot by multiple columns. The resulting table has columns for every unique combination of those columns.

There is no native unpivot clause or function.

Order By

select Col1 order by Col2 desc

The order by clause is used to sort the rows by the values in specified columns. Ascending and descending is specified using asc and desc respectively.

Items in an order by clause can be column identifiers, or the output of aggregation functions, scalar functions, or operators.

Skipping

select Col1 skipping 2

The skipping clause is used to select every nth row, starting from row 1 (i.e. row 1 is always included). This also means that skipping 1 has no effect. If an offset clause is used, skipping is applied first.

Limit

select Col1 limit 5

The limit clause is used to limit the number of returned rows. It can only accept integers.

Offset

select Col1 offset 5

The offset clause is used to skip a given number of first rows. If a limit clause is used, offset is applied first: for example, limit 15 offset 30 returns rows 31 through 45.

Label

select Col1 label Col1 'Name'

The label clause is used to set the label for one or more columns. Note that you cannot use a label value in place of an ID in a query.

Items in a label clause can be column identifiers, or the output of aggregation functions, scalar functions, or operators.

Format

select Col1 format Col1 'mmm'

The format clause is used to specify a formatted value for cells in one or more columns. The returned data should include both an actual value and a formatted value for each cell in a formatted column.

Options

select Col1 options no_values

The options clause is used to control additional options for query execution. Possible keywords that can follow the options clause are:

no_format Removes formatted values from the result, and leaves only the underlying values. Can be used when the specific visualization does not use the formatted values to reduce the size of the response.
no_values Removes underlying values from the result, and leaves only the formatted values. Can be used when the specific visualization uses only the formatted values to reduce the size of the response.

Data Manipulation Functions

Aggregation Functions

Aggregation functions are passed a single column identifier, and perform an action across all values in each group (groups are specified by group by or pivot clauses, or all rows if those clauses are not used).

Aggregation functions can be used in select, order by, label, format clauses. They cannot appear in where, group by, pivot, limit, offset, or options clauses.

Name	Description	Supported Column Types	Return Type
`avg()`	Returns the average value of all values in the column for a group.	`number`	`number`
`count()`	Returns the count of elements in the specified column for a group. Null cells are not counted.	Any type	`number`
`max()`	Returns the maximum value in the column for a group. Dates are compared with earlier being smaller, `string`s are compared alphabetically, with case-sensitivity.	Any type	Same type as column
`min()`	Returns the minimum value in the column for a group. Dates are compared with earlier being smaller, `string`s are compared alphabetically, with case-sensitivity	Any type	Same type as column
`sum()`	Returns the sum of all values in the column for a group.	`number`	`number`

Scalar Functions

Scalar functions return literals by operating over zero or more parameters.

Scalar functions can be used in any of the following clauses: select, where, group by, pivot, order by, label, and format.

Name
`year()`	Returns the year value from a date or datetime value. For example: `year(date "2009-02-05")` returns 2009. Parameters: One parameter of type `date` or `datetime` Return Type: `number`
`month()`	Returns the zero-based month value from a date or datetime value. For example: `month(date "2009-02-05")` returns 1. Note: the months are 0-based, so the function returns 0 for January, 1 for February, etc. Parameters: One parameter of type `date` or `datetime` Return Type: `number`
`day()`	Returns the day of the month from a `date` or datetime value. For example: `day(date "2009-02-05")` returns 5. Parameters: One parameter of type `date` or `datetime` Return Type: `number`
`hour()`	Returns the hour value from a datetime or `timeofday` value. For example: `hour(timeofday "12:03:17")` returns 12. Parameters: One parameter of type `datetime` or `timeofday` Return Type: `number`
`minute()`	Returns the minute value from a `datetime` or `timeofday` value. For example: `minute(timeofday "12:03:17")` returns 3. Parameters: One parameter of type `datetime` or `timeofday` Return Type: `number`
`second()`	Returns the second value from a `datetime` or `timeofday` value. For example: `second(timeofday "12:03:17")` returns 17. Parameters: One parameter of type `datetime` or `timeofday` Return Type: `number`
`millisecond()`	Returns the millisecond part of a `datetime` or `timeofday` value. For example: `millisecond(timeofday "12:03:17.123")` returns 123. Parameters: One parameter of type `datetime` or `timeofday` Return Type: `number`
`quarter()`	Returns the quarter from a `date` or `datetime` value. For example: `quarter(date "2009-02-05")` returns 1. Note that quarters are 1-based, so the function returns 1 for the first quarter, 2 for the second, etc. Parameters: One parameter of type `date` or `datetime` Return Type: `number`
`dayOfWeek()`	Returns the day of week from a `date` or `datetime` value. For example: `dayOfWeek(date "2009-02-26")` returns 5. Note that days are 1-based, so the function returns 1 for Sunday, 2 for Monday, etc. Parameters: One parameter of type `date` or `datetime` Return Type: `number`
`now()`	Returns a datetime value representing the current `datetime` in the GMT timezone. Parameters: None Return Type: `datetime`
`dateDiff()`	Returns the difference in days between two `date` or `datetime` values. Note: Only the `date` parts of the values are used in the calculation and thus the function always returns an integer value. For example: `dateDiff(date "2008-03-13", date "2008-02-12")` returns 29; `dateDiff(date "2009-02-13", date "2009-03-13")` returns -29. Time values are truncated before comparison. Parameters: Two parameters of type `date` or `datetime` (can be one of each) Return Type: `number`
`toDate()`	Transforms the given value to a `date` value. - Given a `date`, it returns the same value. - Given a `datetime`, it returns the `date` part. For example: `toDate(dateTime "2009-01-01 12:00:00")` returns "2009-01-01". - Given a `number` N, it returns a `date` N milliseconds after the Epoch. The Epoch is defined as January 1,1970, 00:00:00 GMT. For example: `toDate(1234567890000)` returns "2009-02-13". Parameters: One parameter of type `date`, `datetime`, or `number` Return Type: `date`
`upper()`	Returns the given `string` in upper case letters. For example: `upper("foo")` returns "FOO". Parameters: One parameter of type `string` Return Type: `string`
`lower()`	Returns the given `string` in lower case letters. For example: `lower("Bar")` returns "bar". Parameters: One parameter of type `string` Return Type: `string`

Arithmetic Operators

The arithmetic operators +, -, *, and / all function as if [[Array operations|array-enabled]]. They can only operate on numbers and accept both vectors and scalars.

Language Elements

Literals

Type	Format
`string`	A `string` literal should be enclosed in either single or double quotes. Examples: `"fourteen" 'hello world' "It's raining"`.
`number`	Numeric literals are specified in decimal notation. Examples: `3 3.0 3.14 -71 -7.2 .6	`
`boolean`	Boolean literals are either `true` or `false`.
`date`	Use the keyword `date` followed by a `string` literal in the format `yyyy-MM-dd`. Example: `date "2008-03-18"`.
`timeofday`	Use the keyword `timeofday` followed by a `string` literal in the format `HH:mm:ss[.SSS]` Example: `timeofday "12:30:45"`.
`datetime`	A date and a time, using either the keyword `datetime` or the keyword `timestamp` followed by a `string` literal in the format `yyyy-MM-dd HH:mm:ss[.sss]`. Example: `datetime '2008-03-18 12:30:34.123'`

Identifiers

Identifiers refer to columns. There are only two valid identifier constructions in Google Sheets, which depend on whether the input is a [[virtual array]] or [[range]].

Input Type	Format	Description
[[Virtual array]]	`Col#`	The `#` refers to the column index of the input.
[[Range]]	`AZ`	You can use a column letter as long as range data is provided.

The QUERY Function