programm 5

Implement an R program to create a histogram illustrating the distribution of a continuous variable with overlaya of desitny curves for each group using ggplot2.

Step 1: load necessary libraries

library(ggplot2)

Step 2: load required dataset

str(iris)#structure of dataset is given using 'str'

'data.frame':   150 obs. of  5 variables:
 $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
 $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
 $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
 $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
 $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...

head(iris)

  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5          1.4         0.2  setosa
2          4.9         3.0          1.4         0.2  setosa
3          4.7         3.2          1.3         0.2  setosa
4          4.6         3.1          1.5         0.2  setosa
5          5.0         3.6          1.4         0.2  setosa
6          5.4         3.9          1.7         0.4  setosa

Step 3: create histogram with group-wise density curves

Step 3.1: intialize the ggplot with asethetic mapping

p<-ggplot(data=iris,aes(x=Petal.Length,fill=Species))
p

Step3.2:add histogram layers

p<-p+geom_histogram(aes(y= ..density..),
                    alpha=0.4,
                    position="identity",
                    bins=30)
p

Warning: The dot-dot notation (`..density..`) was deprecated in ggplot2 3.4.0.
ℹ Please use `after_stat(density)` instead.

Step 3.3: add a density curve layer

p<-p+ geom_density(aes(color=Species),
                   size=1.2)

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.

p

Step 3.4: labs declaration

p<-p+labs(
  title="distribution of petal length with group-wise density curves",
  x="petal length",
  y="density",
  fill="Species"
)+
theme_minimal()
p