PROG2

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 will have the sepal and petal measurements.

• head(data) ,it displays the first few rows.

data <- iris

head(data)

  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 a Scatter plot

Here graphical plot will be displayed.

ggplot(data, aes(x= Sepal.Length, y= Sepal.Width, color= Species))+
  geom_point(size= 3, alpha = 0.7)+
  labs(title= "Scatter plot of dimensions",
       x = "sepal length",
       y = "Sepal width",
       color = "species")+
  theme_minimal()+
  theme(legend.position = "top")