## OVERVIEW:

Data science is a vital tool for any organisation today since it enables the analysis and improvement of decisions and strategy. Thanks to its open source nature, simplicity, application to data analysis, and the number of libraries for any sort of method, R has emerged as the ideal software for data science. We make our data easier to grasp by using components like scatter plots, charts, graphs, histograms, maps, etc. It is simple to spot patterns, trends, and exceptions in our data thanks to data visualisation. It helps us to quickly and visually communicate information and results. Information given in a visual format is simpler for the human brain to comprehend and remember. Data visualisation enables us to easily evaluate data, look at various variables to determine how they affect the patterns, and draw conclusions from our data. This book is intended for students who wish to thoroughly understand the principles of the R programming language as well as some of the best libraries for data visualisation in the form of charts, graphs, and maps. Through examples and practise, the reader will master the language and applications. No prior programming experience is necessary. The installation and setting of the R environment using RStudio is covered at the beginning of the book. You will gain a complete understanding of R’s features and the well-known tidyverse package as you work your way through the tasks in this practical book. With the help of this book, you will become familiar with the fundamental ideas behind R programming, learn how to use graphs, charts, and maps effectively, and produce papers that are ready for publishing using actual data. You will be able to obtain a clean set of data, build captivating visualisations, and prepare reports on the outcomes thanks to the comprehensive step-by-step instructions. Data visualisation is useful despite the aforementioned drawbacks since it facilitates intuitive and simple understanding of massive amounts of data, allowing for better decision-making. Hope you will find this book both helpful and beneficial.

## Topics covered by this book:

- Chapter 1 is Introduction to R and RStudio. In this chapter you will get a detail Introduction to the R programming language and R Studio.

- Chapter 2 is about The Basics of Data Exploration. You will learn how to use the tidyverse package for data loading, transformation, as well as visualization.

- Chapter 3 is Loading Data into R. In this chapter you will learn about the most important data structures in R.

- Chapter 4 is Transforming Data. In this chapter you will learn about techniques for importing data, performing analysis, manipulating data, as well as producing useful data visualization.

- Chapter 5 and 6 is Creating Tidy Data and Basic Data Exploration Techniques in R. It all about Gathering, spreading, separating as well as uniting.

- Chapter 7 and 8 is about Basic Data visualization Techniques and Visualizing Geographic Data with ggmap. This is about Data visualization techniques with ggplot2. It is about Geographic visualization and maps with ggmap.

- Chapter 9 is about R Markdown. It is about learn about how to Turnyour analyses into high quality documents, reports, and presentations with R Markdown.

- The end is about case studies. Hands on case studies designed to replicate real world projects and reinforce the knowledge you learn in the book.