Program 5

Author

Stephen George

USN:

1NT24IS227

RPubs Link:

https://rpubs.com/Stephen__/1413724

Problem statement:

Implement a R program to create a histogram illustrating the distribution of a continuous variable, with overlays of density curves for each hroup, using ggplot2.

Step 1: Load Required Library

We first load the ggplot2 package, which is used for data visualization in R.

#load ggplot2 package for visualization
library(ggplot2)

Step 2: Explore the Inbuilt Dataset

We use the built-in dataset. In this dataset:

#use the built-in `iris` dataset
# `Petal.Length` is a continuous variable
# `Species` is a categorical grouping variable

str(iris)

'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

head(iris, n=2)

  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

tail(iris)

    Sepal.Length Sepal.Width Petal.Length Petal.Width   Species
145          6.7         3.3          5.7         2.5 virginica
146          6.7         3.0          5.2         2.3 virginica
147          6.3         2.5          5.0         1.9 virginica
148          6.5         3.0          5.2         2.0 virginica
149          6.2         3.4          5.4         2.3 virginica
150          5.9         3.0          5.1         1.8 virginica

tail(iris, n=2)

    Sepal.Length Sepal.Width Petal.Length Petal.Width   Species
149          6.2         3.4          5.4         2.3 virginica
150          5.9         3.0          5.1         1.8 virginica

Step 3.1

# STart ggplot with iris dataset
# Map Petal.Length to x-axis and fill by Species

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

Step 3.2

# Add histogram with density scaling

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.

Explanation

Step 3.3

# Overlay density curves for each group

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.

Step 3.4

Now we improve the appearance of the graph

# Add title and axis labels, and apply clean theme

p <- p + labs(
  title = "Distribution of Petal Length with Group-wise Density Curves",
  x= "Petal Length",
  y = "Density")+
  theme_minimal()

p