Creating a correlation matrix
We will take a sample dataset for explaining our approach better. We will take the inbuilt USArrests dataset, and we will visualize its correlation matrix following the above approach. We will read the data using the data() function, and we will create the correlation matrix with the help of cor() function to compute the correlation coefficient. The round() function is used to round off the values to a specific decimal value. We will use cor_pmat() function to compute the correlation matrix with p-values.
Syntax :
correlation_matrix <- round(cor(data),1)
Parameters :
- correlation_matrix : Variable for correlation matrix used to visualize.
- data : data is our dataset which we have taken for visualization.
Syntax:
corrp.mat <- cor_pmat(data)
Parameters :
- corrp.mat : Variable for correlation matrix with p-values.
- data : It is our dataset taken for creating correlation matrix with p-values.
Example: Creating a correlation matrix
R
# Installing and loading the ggcorrplot package install.packages("ggcorrplot") library(ggcorrplot) # Reading the data data(USArrests) # Computing correlation matrix correlation_matrix <- round(cor(USArrests),1) head(correlation_matrix[, 1:4]) # Computing correlation matrix with p-values corrp.mat <- cor_pmat(USArrests) head(corrp.mat[, 1:4]) |
Output :
Visualization of a correlation matrix using ggplot2 in R
In this article, we will discuss how to visualize a correlation matrix using ggplot2 package in R programming language.
In order to do this, we will install a package called ggcorrplot package. With the help of this package, we can easily visualize a correlation matrix. We can also compute a matrix of correlation p-values by using a function that is present in this package. The corr_pmat() is used for computing the correlation matrix of p-values and the ggcorrplot() is used for displaying the correlation matrix using ggplot.
Syntax :
corr_pmat(x,..)
Where x is the dataframe or the matrix
Syntax:
ggcorrplot(corr, method = c(“circle”, “square”), type = c(“full”, “lower”, “upper”), title = “”, ggtheme=ggplot2::theme_minimal, show.legend = TRUE, legend.title = “corr”, show.diag = FALSE, colors = c(“blue”, “white”, “red”), outline.color = “gray”, hc.order = FALSE, hc.method = “complete”, lab = FALSE, lab_col =”black”, p.mat = NULL,.. )
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