ggInterval_scaMatrix {ggESDA} | R Documentation |
scatter plot for all variable by interval data.
Description
Visualize the all continuous variable distribution by rectangle for both x-axis and y-axis with a matrix grid. Note: this function will automatically filter out the discrete variables,and plot all continuous in input data,so it can not be necessary that give the particularly variables in aes such like (aes(x = x, y = y)). It isn't also recommended to deal with too many variables because the big O in calculating full matrix will be too large.
Usage
ggInterval_scaMatrix(data = NULL,mapping = aes(NULL), showLegend=FALSE)
Arguments
data |
A ggESDA object. It can also be either RSDA object or classical data frame,which will be automatically convert to ggESDA data. |
mapping |
Set of aesthetic mappings created by aes() or aes_(). If specified and inherit. aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping. |
showLegend |
whether show the legend. |
Value
Return a plot with no longer a ggplot2 object,instead of a marrangeGrob object.
Examples
a<-rnorm(1000,0,5)
b<-runif(1000,-20,-10)
c<-rgamma(1000,10,5)
d<-as.data.frame(cbind(norm=a,unif=b,gamma_10_5=c))
ggInterval_scaMatrix(d)
ggInterval_scaMatrix(mtcars[,c("mpg","wt","qsec")],
aes(col="red",lty=2,fill="blue",alpha=0.3))
myIris <- classic2sym(iris,groupby = "Species")$intervalData
ggInterval_scaMatrix(myIris[,1:3])
mydata <- ggESDA::Cardiological
ggInterval_scaMatrix(mydata[,1:3],aes(fill="black",alpha=0.2))