Class 4

iris = read.csv('iris.csv')
iris

library(ggplot2)
ggplot(iris, aes(x=sepal.length))+
  geom_histogram()

`stat_bin()` using `bins = 30`. Pick
better value with `binwidth`.

##Correlation Matrix

#must numeric value
#cor_mat = cor(iris[,c(1,2,3,4)])
cor_mat = cor(iris[,1:4])
cor_mat

             sepal.length sepal.width petal.length petal.width
sepal.length    1.0000000  -0.1175698    0.8717538   0.8179411
sepal.width    -0.1175698   1.0000000   -0.4284401  -0.3661259
petal.length    0.8717538  -0.4284401    1.0000000   0.9628654
petal.width     0.8179411  -0.3661259    0.9628654   1.0000000

Heat Map

library(ggcorrplot)
ggcorrplot(cor_mat)

ggcorrplot(cor_mat,type='lower',colors =c('red','white','pink'))

ggcorrplot(cor_mat,type='lower',colors =c('green','white','pink'),
           lab=TRUE
           )