How to compute Correlation Matrix and Visualize it in R?

Description

To compute the correlation matrix and visualize it using R programming.

Correlation:

   A correlation is a single number
  that describes the degree of relationship
 between two variables.

Correlation Matrix:

   A correlation matrix is a table showing
 correlationcoefficients between
 sets of variables

   R Function : cor(Data Frame)

Correlation Matrix with significance
 levels:

   R Package : Hmisc

   R Function :rcorr(Correlation Matrix)

Methods for Visualizing Correlation
 Matrix:

   corrplot()function to plot Correlogram

   symnum()function

   Scatter plot

#Correlation and Correlation Matrix

#Get and Set Working Directory
print(getwd())
setwd(“/home/soft13″)
getwd()

#Read file from Excel
#install.packages(“xlsx”)
library(“xlsx”)
my_data<-read.xlsx(“mtcars.xlsx”,sheetIndex=1)
my_data1<-mtcars[,c(“mpg”,”disp”,”hp”,”wt”)]
View(my_data1)

#Compute Correlation Matrix
input<-cor(my_data1)
print(input)

#Correlation Matrix with significance levels
#install.packages(“Hmisc”)
library(“Hmisc”)
input1<-rcorr(as.matrix(my_data1))
print(input1)

#Extracting Correlation Coefficients and P- Values
round(input1$r,2)
input1$P

#Formatting Correlation Matrix

formatCorMat<-function(corr,pval){
upper<-upper.tri(corr)
data.frame(
Row = rownames(corr)[row(corr)[upper]],
Column = colnames(corr)[col(corr)[upper]],
CorrelationCoef = corr[upper],
P_Value = pval[upper],
stringsAsFactors = FALSE
)
}
formatCorMat(input1$r,input1$P)

#Visualizing Correlation Matrix
#Corrplot()
library(“corrplot”)
corrplot(input,tl.col = “Black”,type=”upper”)
#symnum()
symnum(input, abbr.colnames = FALSE)

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