analytics-dimension {khisr}

Analytics Data Dimensions

Description

Constructs a dimensions expression for analytics queries based on specified property, operator, and values.

Usage

analytics_dimension(property, operator, values)

operator %.d% values

operator %.f% values

Arguments

property

A character string representing whether its dimension or filter. It only accepts 'dimension', 'filter'.

operator

A character string representing the property to filter on (e.g., 'dx', 'pe', 'ou').

values

A vector of values or semi-colon separated string items.

Details

DHIS2 organizes data using multiple dimensions, each with a unique identifier and a set of items that represent specific data points within that dimension.

• Data elements (dx): Indicators, data set reporting rate metrics, data element operands, program indicators, program data elements, program attributes, validation rules.

• Periods (pe): ISO periods (e.g., 202401) and relative periods (e.g., LAST_WEEK).

• Organisation unit hierarchy (ou): Specific health facilities, districts, countries, and keywords for user location or its sub-units.

• Category option combinations (co): Category option combo identifiers.

• Attribute option combinations (ao): Category option combo identifiers.

• Categories: Category option identifiers.

• Data element group sets: Data element group identifiers.

• Organisation unit group sets: Organisation unit group identifiers.

The infix operator used for filter and dimension includes:

• ⁠%.d%⁠: Infix operator for constructing dimension filters. Equivalent to calling analytics_dimension("dimension", ...).

• ⁠%.f%⁠: Infix operator for constructing filter filters. Equivalent to calling analytics_dimension("filter", ...).

Value

A spliced list with filter in the format property=operator:value

Examples

# Create a dimension for data element "DE_1234"
analytics_dimension('dimension', "dx", "DE_1234")

# Equivalent to the expression above
dx %.d% "DE_1234"

# Create a filter dimension for the period of January 2024
pe %.f% "202401"

# Create filter dimension for periods "202401" and "202402":
analytics_dimension("filter", "pe", c("202401", "202402"))