program2_dv

Write an R script to create a scatter plot, incorporating categorical analysis through color-coded data points representing different groups, using ggplot2.

Step 1: Load necessary libraries

library(ggplot2)
library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Step 2: Load the Data set

Explanation:

• The iris dataset contains 150 samples of iris flowers categorized into three species: setosa, versicolor and virginica.

• Each sample has sepal and petal

• head(data) displays the first six rows

data <- iris
head(data, n=10) #first six rows of the dataset by default

   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
7           4.6         3.4          1.4         0.3  setosa
8           5.0         3.4          1.5         0.2  setosa
9           4.4         2.9          1.4         0.2  setosa
10          4.9         3.1          1.5         0.1  setosa

table(data$Species)

    setosa versicolor  virginica 
        50         50         50 

Step 3: Create a Scatter Plot

ggplot(data, aes(x= Sepal.Length, y= Sepal.Width, color=Species))+
  geom_point(size=3, alpha=0.7)+
  labs(title= "Scatter Plot of Sepal Dimensions", 
       x="Sepal Length",
       y="Sepal Width", 
       color = "Species") + #Legend title
  theme_minimal() +         #Clean title
  theme(legend.position = "top")  #Move legend to the top