wk 8

2023-02-28

# load the ggplot2 library
library(ggplot2)
library(reshape2)
# calculate the correlation matrix
correlation_matrix = cor(mtcars)

# create a heatmap of the correlation matrix
ggplot(data = melt(correlation_matrix), aes(x = Var1, y = Var2, fill = value)) +
  geom_tile() +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

#The code loads the ggplot2 and reshape2 libraries and uses the cor function to calculate the correlation matrix of the mtcars dataset. Then, it creates a heatmap of the correlation matrix using ggplot, where the x and y axes represent the variable names and the fill represents the correlation value. The geom_tile() function is used to create the heatmap, while the theme_minimal() function is used to set the theme to a minimal design. Additionally, the theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) is used to rotate the x-axis text labels by 90 degrees to make them more readable.