View source: R/fn_exp_ParCoordPlot.R
ExpParcoord | R Documentation |
This function creates parallel Co ordinate plots
ExpParcoord(
data,
Group = NULL,
Stsize = NULL,
Nvar = NULL,
Cvar = NULL,
scale = NULL
)
data |
Input dataframe or data.table |
Group |
stratification variables |
Stsize |
vector of startum sample sizes |
Nvar |
vector of numerice variables, default it will consider all the numeric variable from data |
Cvar |
vector of categorical variables, default it will consider all the categorical variable |
scale |
scale the variables in the parallel coordinate plot (Default normailized with minimum of the variable is zero and maximum of the variable is one) (see ggparcoord details for more scale options) |
The Parallel Co ordinate plots having the functionalities of visulization for sample rows if data size large. Also data can be stratified basis of Target or group variables. It will normalize all numeric variables between 0 and 1 also having other standardization options. It will automatically make dummy (1,0) variables for categorical variables
Parallel Co ordinate plots
ggparcoord
CData = ISLR::Carseats
# Defualt ExpParcoord funciton
ExpParcoord(CData,Group=NULL,Stsize=NULL,
Nvar=c("Price","Income","Advertising","Population","Age","Education"))
# With Stratified rows and selected columns only
ExpParcoord(CData,Group="ShelveLoc",Stsize=c(10,15,20),
Nvar=c("Price","Income"),Cvar=c("Urban","US"))
# Without stratification
ExpParcoord(CData,Group="ShelveLoc",Nvar=c("Price","Income"),
Cvar=c("Urban","US"),scale=NULL)
# Scale changed std: univariately, subtract mean and divide by standard deviation
ExpParcoord(CData,Group="US",Nvar=c("Price","Income"),
Cvar=c("ShelveLoc"),scale="std")
# Selected numeric variables
ExpParcoord(CData,Group="ShelveLoc",Stsize=c(10,15,20),
Nvar=c("Price","Income","Advertising","Population","Age","Education"))
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