mosaic.dt: Mosaic plot as data.table

In VEuPathDB/plot.data: Create `data.table`s of Ready to Plot Data

Mosaic plot as data.table

Description

This function returns a data.table of plot-ready data with one row per panel. Columns 'x' and 'y' contain the raw data for plotting. Column 'panel' specifies the panel the data belongs to.

Usage

mosaic.dt(
  data,
  variables,
  statistic = NULL,
  columnReferenceValue = NA_character_,
  rowReferenceValue = NA_character_,
  overlayValues = NULL,
  sampleSizes = c(TRUE, FALSE),
  completeCases = c(TRUE, FALSE),
  evilMode = c("noVariables", "allVariables", "strataVariables"),
  verbose = c(TRUE, FALSE)
)

Arguments

data	data.frame to make plot-ready data for
variables	veupathUtil::VariableMetadataList
statistic	String indicating which statistic to calculate. Vaid options are 'chiSq' and 'all', the second of which will return odds ratios and relative risk.
columnReferenceValue	String representing a value present in the column names of the contingency table
rowReferenceValue	String representing a value present in the row names of the contingency table
overlayValues	veupathUtils::BinList providing overlay values of interest
sampleSizes	boolean indicating if sample sizes should be computed
completeCases	boolean indicating if complete cases should be computed
evilMode	String indicating how evil this plot is ('strataVariables', 'allVariables', 'noVariables')
verbose	boolean indicating if timed logging is desired

Value

data.table plot-ready data

Evil Mode

An 'evilMode' exists. It will do the following:
- when ‘strataVariables' it will return ’no data' as a regular value for strata vars but will discard such cases for the axes vars.
- when ‘allVariables' it will return ’no data' as a regular value for all variables.
- when 'noVariables' it will do the sensible thing and return complete cases only.
- not return statsTables
- allow smoothed means and agg values etc over axes values where we have no data for the strata vars
- return a total count of plotted incomplete cases
- represent missingness poorly, conflate the stories of completeness and missingness, mislead you and steal your soul

Examples

# Construct example data
df <- data.table('entity.xvar' = sample(c('a','b','c'), 100, replace=T),
                 'entity.yvar' = sample(c('1','2','3'), 100, replace=T), stringsAsFactors = F)

# Create VariableMetadataList that specifies variable role in the plot and supplies variable metadata
variables <- veupathUtils::VariableMetadataList(
  veupathUtils::VariableMetadata(
    variableClass = veupathUtils::VariableClass(value = 'native'),
    variableSpec = veupathUtils::VariableSpec(variableId = 'xvar', entityId = 'entity'),
    plotReference = veupathUtils::PlotReference(value = 'xAxis'),
    dataType = veupathUtils::DataType(value = 'STRING'),
    dataShape = veupathUtils::DataShape(value = 'CATEGORICAL')
  ),
  veupathUtils::VariableMetadata(
    variableClass = veupathUtils::VariableClass(value = 'native'),
    variableSpec = veupathUtils::VariableSpec(variableId = 'yvar', entityId = 'entity'),
    plotReference = veupathUtils::PlotReference(value = 'yAxis'),
    dataType = veupathUtils::DataType(value = 'STRING'),
    dataShape = veupathUtils::DataShape(value = 'CATEGORICAL')
  )
)

# Returns a data table with plot-ready data
dt <- mosaic.dt(df, map)

VEuPathDB/plot.data documentation built on Feb. 20, 2025, 6:33 p.m.