PART A
1) Develop an r program to quickly explore a given dataset , including categorical analysis using the graph_by() command, and visualize the findings using ggplot2 . what we will do In this program, we will: Load the required libraries and dataset. Explore the structure of the dataset. Convert a numerical variable into a categorical variable. Perform categorical analysis using group_by() and summarize() . Visual the result using ggplot2 . step1 : Load required libraries and dataset tidyverse is a collection of packages for data science. dplyr is used for grouping and summarizing data. {r} library(tidyverse) library(dplyr) data <- mtcars Step 2: Explore the dataset Before performing any analysis, we should understand the dataset. we will check: Number of rows and columns Columns name Data types Summary statistics First few rows {r} # Dimension (rows and columns) dim(data) # Column names names(data) # structure of dataset str(data) # Summary statistics summary(d...