In a quality statistical data analysis the initial step has to be exploratory. Exploratory data analysis begins with the univariate exploratory analyis - examining the variable one at a time. Next comes bivariate analysis followed by multivariate analyis. SmartEDA package helps in getting the complete exploratory data analysis just by running the function instead of writing lengthy r code.
The package can be installed directly from CRAN.
install.packages("SmartEDA")You can install SmartEDA from github with:
{r gh-installation, eval = FALSE} # install.packages("devtools") devtools::install_github("cran/SmartEDA")
In this vignette, we will be using a simulated data set containing sales of child car seats at 400 different stores.
Data Source ISLR package.
Install the package “ISLR” to get the example data set.
install.packages("ISLR")
library("ISLR")
install.packages("SmartEDA")
library("SmartEDA")
## Load sample dataset from ISLR pacakge
Carseats= ISLR::CarseatsUnderstanding the dimensions of the dataset, variable names, overall missing summary and data types of each variables
ExpData(data=Carseats,type=1)
ExpData(data=Carseats,type=2)To summarise the numeric variables, you can use following r codes from this pacakge
ExpNumStat(Carseats,by="A",gp=NULL,Qnt=seq(0,1,0.1),MesofShape=2,Outlier=TRUE,round=2)
ExpNumStat(Carseats,by="A",gp="Price",Qnt=seq(0,1,0.1),MesofShape=1,Outlier=TRUE,round=2)
ExpNumStat(Carseats,by="GA",gp="Urban",Qnt=seq(0,1,0.1),MesofShape=2,Outlier=TRUE,round=2)ExpNumViz(Carseats,gp=NULL,nlim=10,Page=c(2,2),sample=8)
ExpNumViz(Carseats,gp="Urban",type=1,nlim=NULL,fname=NULL,col=c("pink","yellow","orange"),Page=c(2,2),sample=8) ExpCTable(Carseats,Target=NULL,margin=1,clim=10,nlim=5,round=2,bin=NULL,per=T)
ExpCatViz(Carseats,gp=NULL,fname=NULL,clim=10,margin=2,Page = c(2,1),sample=4)
ExpCTable(Carseats,Target="Price",margin=1,clim=10,nlim=NULL,round=2,bin=4,per=F)
ExpCatStat(Carseats,Target="Urban",Label="Store Location",result = "Stat",clim=10,nlim=5,Pclass="Yes")
ExpCatStat(Carseats,Target="Urban",Label="Store Location",result = "IV",clim=10,nlim=5,Pclass="Yes")
ExpCTable(Carseats,Target="Urban",margin=1,clim=10,nlim=NULL,round=2,bin=NULL,per=F)ExpCatViz(Carseats,gp="Urban",fname=NULL,clim=10,col=NULL,margin=2,Page = c(2,1),sample=2)Create a exploratory data analysis report in HTML format
ExpReport(Carseats,Target="Urban",label=NULL,op_file="test.html",op_dir=getwd(),sc=2,sn=2,Rc="Yes")Descriptive summary on all input variables for each level/combination of group variable. Also while running the analysis we can filter row/cases of the data.
ExpCustomStat(Carseats,Cvar=c("US","Urban","ShelveLoc"),gpby=FALSE)
ExpCustomStat(Carseats,Cvar=c("US","Urban"),gpby=TRUE,filt=NULL)
ExpCustomStat(Carseats,Cvar=c("US","Urban","ShelveLoc"),gpby=TRUE,filt=NULL)
ExpCustomStat(Carseats,Cvar=c("US","Urban"),gpby=TRUE,filt="Population>150")
ExpCustomStat(Carseats,Cvar=c("US","ShelveLoc"),gpby=TRUE,filt="Urban=='Yes' & Population>150")
ExpCustomStat(Carseats,Nvar=c("Population","Sales","CompPrice","Income"),stat = c('Count','mean','sum','var','min','max'))
ExpCustomStat(Carseats,Nvar=c("Population","Sales","CompPrice","Income"),stat = c('min','p0.25','median','p0.75','max'))
ExpCustomStat(Carseats,Nvar=c("Population","Sales","CompPrice","Income"),stat = c('Count','mean','sum','var'),filt="Urban=='Yes'")
ExpCustomStat(Carseats,Nvar=c("Population","Sales","CompPrice","Income"),stat = c('Count','mean','sum'),filt="Urban=='Yes' & Population>150")
ExpCustomStat(data_sam,Nvar=c("Population","Sales","CompPrice","Income"),stat = c('Count','mean','sum','min'),filt="All %ni% c(999,-9)")
ExpCustomStat(Carseats,Nvar=c("Population","Sales","CompPrice","Education","Income"),stat = c('Count','mean','sum','var','sd','IQR','median'),filt=c("ShelveLoc=='Good'^Urban=='Yes'^Price>=150^ ^US=='Yes'"))
ExpCustomStat(Carseats,Cvar = c("Urban","ShelveLoc"), Nvar=c("Population","Sales"), stat = c('Count','Prop','mean','min','P0.25','median','p0.75','max'),gpby=FALSE)
ExpCustomStat(Carseats,Cvar = c("Urban","US","ShelveLoc"), Nvar=c("CompPrice","Income"), stat = c('Count','Prop','mean','sum','PS','min','max','IQR','sd'), gpby = TRUE)
ExpCustomStat(Carseats,Cvar = c("Urban","US","ShelveLoc"), Nvar=c("CompPrice","Income"), stat = c('Count','Prop','mean','sum','PS','P0.25','median','p0.75'), gpby = TRUE,filt="Urban=='Yes'")
ExpCustomStat(data_sam,Cvar = c("Urban","US","ShelveLoc"), Nvar=c("Sales","CompPrice","Income"), stat = c('Count','Prop','mean','sum','PS'), gpby = TRUE,filt="All %ni% c(888,999)")
ExpCustomStat(Carseats,Cvar = c("Urban","US"), Nvar=c("Population","Sales","CompPrice"), stat = c('Count','Prop','mean','sum','var','min','max'), filt=c("ShelveLoc=='Good'^Urban=='Yes'^Price>=150"))