Machine Learning - Data visualization with R (III)

Machine Learning - Data visualization with R (III)

?? Fernando Bucci ?? Fernando Bucci

?? Fernando Bucci

Head of Gen AI for Software Engineering

发布日期: 2017年12月7日
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This article continues presenting different techniques that can be used to communicate data or information by encoding it in graphs.


Correlogram

Correlogram is a graph of the correlation matrix. It is useful to highlight the most correlated variables.

# Load packages
install.packages("ggplot2");library("ggplot2");
install.packages("corrplot");library("corrplot");
install.packages("RColorBrewer");library("RColorBrewer");

#Color
corrplot(cor(mtcars), method="color", type="upper", order="hclust", 
  addCoef.col="black", col=brewer.pal(n=8, name="RdYlBu"),
  tl.col="black", tl.srt=45, sig.level=0.2, insig = "blank", diag=FALSE)

#Pies
corrplot(cor(mtcars), method="pie", type="upper", order="hclust",
  col=brewer.pal(n=8, name="RdYlBu"),
  tl.col="black", tl.srt=45, sig.level=0.2, insig="blank", diag=FALSE)

#Ellipses
corrplot(cor(mtcars), method="ellipse", type="upper", order="hclust",
  col=brewer.pal(n=8, name="RdYlBu"),
  tl.col="black", tl.srt=45, sig.level=0.2, insig="blank", diag=FALSE)

#Circles, ignore low significance, create 2 groups.
res <- cor.mtest(mtcars, conf.level=.95)
corrplot(cor(mtcars), method="circle", 
  order="hclust", addrect=2,
  p.mat=res, sig.level=0.2, 
  col=brewer.pal(n=8, name="RdYlBu"), 
  tl.col="black", tl.srt=45, diag=FALSE)


Many More Graphs and Charts

There is a wide range of charts supported by the already existing powerful R libraries. Here you have some of them:


Try it out, share your experience and provide feedback!

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