Program2

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

# 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 dataset

Explanation:

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

• each sample and sepal and petal measurements.

• head(data) display the first few rows.

#Load the iris dataset
data<-iris

#display first few rows
head(data, n=10)

   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

#create a scatter plot using ggplot2
ggplot(data, aes(x= Sepal.Length, y=Sepal.Width, color = Species))+ geom_point(size=3, alpha=0.7)+ #Increase point size & transparency
  labs(title="Scatter Plot of Sepal Dimension", x="sepal length", y="sepal width", color= "species")+ #Legend title
  theme_minimal()+ # Clean Layout
  theme(legend.position="top") #move legend to the top