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Overview

You specify how Horizon AI Query should dissect the selected data through a Group By clause. The Aggregate expressions you specify would then be applied to the resulting groups. Your Group By clause can contain one or more of the following expressions: You can mix and match any expression types, and organize them in any order. Group Key Column expression tracks your declaration order.

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Group by a truncated datetime

Group the input rows based on the specified column expression truncated to the specified granularity. This is similar to the DATE_TRUNC function in SQL.

Input argument

Output column name

import vitalx.aggregation as va

# Truncate to every 1 day.
va.select(...).group_by(
    va.date_trunc(va.Sleep.index(), 1, "day"),
)

# Truncate to every 3 months.
va.select(...).group_by(
    va.date_trunc(va.Sleep.index(), 3, "month"),
)

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Group by a date or time component

Group the input rows based on a specific date or time component extracted from the specified column expression. This is similar to the DATE_PART function in SQL.

Input argument

Output column name

import vitalx.aggregation as va

# Extract the weekday
va.select(...).group_by(
    va.date_part(va.Sleep.index(), "weekday"),
)

# Extract the day-of-month
va.select(...).group_by(
    va.date_part(va.Sleep.index(), "day")
)

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Group by a Table Column expression

Group the input rows based on a Table Column expression. This is similar to the generic GROUP BY clause in SQL.

Input argument

Output column name

import vitalx.aggregation as va

# Group by calendar date and Stand Hour type (idle vs stand)

va.select(
    va.group_key("*"),
    va.Timeseries.col("stand_hour").field("value").sum()
).group_by(
    va.date_trunc(va.Timeseries.index(), 1, "day"),
    va.Timeseries.col("stand_hour").field("type")
)

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Group by a Source Column expression

Group the input rows based on a Source Column expression. This is similar to a generic GROUP BY clause in SQL.
If both the Provider and Source Type Source Columns are present in the Group By clause, the implicit Data Prioritization behaviour would be disabled.

Input argument

Output column name

import vitalx.aggregation as va

# Group by the source provider and source type
va.select(...).group_by(
    va.date_trunc(va.Sleep.index(), 1, "week"),
    va.Source.col("source_provider"),
    va.Source.col("source_type")
)