prepNiceData: Prepare and print basic statistics for niceBox and niceVio
In ZachHunter/NicePlots.R: Nice Plots for Data Exploration

prepNiceData

R Documentation

Prepare and print basic statistics for niceBox and niceVio

Description

Uses filtred data with subgroup and factor information to calculate quartile data for display and plotting.

Usage

prepNiceData(
  prepedData,
  by,
  subgroup = FALSE,
  outliers = TRUE,
  filter,
  groupLabels,
  plotLoc,
  width = 1,
  flipFacts = FALSE,
  verbose = FALSE
)

Arguments

`prepedData`	list; a list object returned by `prepCategoryWindow`
`by`	factor or dataframe of factors; One or more factors that control how the data is grouped. The first column is the primary grouping factor and the second and thrid columns are used for sub-grouping and highlighting as needed.
`subgroup`	logical; Should the data be faceted into subgroups within the primary factor levels. Ignored if `by` is a `factor`.
`outliers`	positive numeric; number of interquartile ranges (IQR) past the Q1 (25%) and Q3 (75%) cumulative distribution values. Outliers are often defined as `1.5 \times IQR` and extreme outliers are more than `3 \times IQR` away from the inner 50% data range.
`filter`	logical vector; Used to further filter the data if necissary.
`groupLabels`	character; A character vector for the primary group names
`plotLoc`	numeric vector; A vector indicating where each element should be plotted
`width`	numeric; A multiplier that controls how wide the ploting elements will be. Setting `width=1.1` would result in plot elements being 10% wider.
`flipFacts`	logical; When a dataframe of values is given, column names are used as a secondary grouping factor by default. Setting `flipFacts=TRUE` makes the column names the primary factor and `by` the secondary factor.
`verbose`	logical; Will print summary statistics to the screen if set to `TRUE`. The function will return the calculations either way.

Details

To aid in data interpretation and exploration, quartile distribution statistics are calculated for each group and subgroup if specified. For niceBox this data is also used to plot the data. The data is parsed by checking outlier and subgroup status as weel as checking if either prepedData or by are a data.frame or a vector.

Examples

data(iris)
filter<-rep(TRUE,length(iris$Species))
loc<-seq(1,length(levels(iris$Species)))
data<-list(data=iris[,1:4])
#\donttest{myData<-prepNiceData(data,by=iris$Species,filter=filter,plotLoc=loc,
#     groupLabels=levels(iris$Species),outliers=FALSE)}
#\donttest{print(myData)}

ZachHunter/NicePlots.R documentation built on Sept. 23, 2023, 4:04 a.m.