#title DataExplorer Package
[[TableOfContents]]

--출처: https://www.r-bloggers.com/how-to-automate-eda-with-dataexplorer-in-r/

==== 설치 ====
{{{
install.packages("DataExplorer")
library(DataExplorer)
}}}

==== 테스트 데이터 만들기 ====
{{{
mydata <- iris
mydata[5:50, 3] <- NA
mydata$Species <- as.factor(mydata$Species)
head(mydata)
}}}

==== 연속형 변수, 이산형 변수, Missing Value ====
{{{
plot_intro(mydata, title = "Automated EDA with Data Explorer")
}}}

attachment:DataExplorerPackage/1.png

==== Missing Value ====
{{{
plot_missing(mydata)
}}}
attachment:DataExplorerPackage/2.png

==== Histogram ====
{{{
plot_histogram(mydata)
}}}
attachment:DataExplorerPackage/3.png

==== Density ====
{{{
plot_density(mydata)
}}}
attachment:DataExplorerPackage/4.png

==== BoxPlot ====
{{{
plot_boxplot(mydata, by= 'Species',  ncol = 2)
}}}
attachment:DataExplorerPackage/5.png

==== Correlation ====
{{{
plot_correlation(mydata, cor_args = list( 'use' = 'complete.obs'))
}}}
attachment:DataExplorerPackage/6.png

{{{
plot_correlation(mydata, type = 'c', cor_args = list( 'use' = 'complete.obs'))
}}}
attachment:DataExplorerPackage/7.png

==== Categorical ====
{{{
plot_bar(mydata$Species, maxcat = 20)
#plot_bar(mydata, maxcat = 20, parallel = TRUE) #Windows OS에서 지원 안됨
}}}
attachment:DataExplorerPackage/8.png

{{{
plot_bar(mydata, with = c("Sepal.Length"), maxcat = 20)
#plot_bar(mydata, with = c("Sepal.Length"), maxcat = 20, parallel = TRUE)
}}}
attachment:DataExplorerPackage/9.png

==== Automating EDA ====
이렇게 하면 {{{Data Profiling Report}}}가 만들어 진다.
{{{
create_report(mydata)
}}}