
Create a visual table of the most common concepts from summariseConceptIdCounts() output
Source: R/tableTopConceptCounts.R
tableTopConceptCounts.RdThis function takes a summarised_result object and generates a formatted
table highlighting the most frequent concepts.
Arguments
- result
A summarised_result object (output of
summariseConceptIdCounts()).- top
Integer. The number of top concepts to display. Defaults to
10.- countBy
Either 'person' or 'record'. If NULL whatever is in the data is used.
- type
Character string specifying the desired output table format. See
visOmopResults::tableType()for supported table types. Iftype = NULL, global options (set viavisOmopResults::setGlobalTableOptions()) will be used if available; otherwise, a default 'gt' table is created.- style
Defines the visual formatting of the table. This argument can be provided in one of the following ways:
Pre-defined style: Use the name of a built-in style (e.g., "darwin"). See
visOmopResults::tableStyle()for available options.YAML file path: Provide the path to an existing .yml file defining a new style.
List of custome R code: Supply a block of custom R code or a named list describing styles for each table section. This code must be specific to the selected table type.
If
style = NULL, the function will use global options (seevisOmopResults::setGlobalTableOptions()) or a _brand.yml file (if found); otherwise, the default style is applied.
Examples
# \donttest{
library(OmopSketch)
library(omock)
cdm <- mockCdmFromDataset(datasetName = "GiBleed", source = "duckdb")
#> ℹ Reading GiBleed tables.
#> ℹ Adding drug_strength table.
#> ℹ Creating local <cdm_reference> object.
#> ℹ Inserting <cdm_reference> into duckdb.
result <- summariseConceptIdCounts(cdm = cdm, omopTableName = "condition_occurrence")
tableTopConceptCounts(result = result, top = 5)
Top 5 concepts in condition_occurrence table
condition_occurrence
cdmDisconnect(cdm = cdm)
# }