Murach's R for Data Analysis

I’ve written ten computer books back in the day, so I know something about the genre. IMHO there are only two currently available series of self-learning computer subject books worth having: any Murach title, and any of the “Heads Up” collection.With this book on R being among the best of them all.

Excellent framework to lead one through a data analysis project. Clearly written and to the point. Of the dozens of R books that I've read, this is in my top five.

I recently read Murach's Python for Data Analysis and wanted to see how it compared to R for Data Analysis. I work with database administration and data analysis and wanted to see how Python and R worked with data analysis. The two books are similar, but I found different strengths in each. If you are looking for more content on data visualization you are likely to like the R book better of the pair. The first section, “Get started fast” really does start with the basics of R Studio and gives a good summary of R Studio. After R Studio, the book goes into some basic R concepts. The second chapter goes much deeper into R coding. Chapter 3 shows how to use R with a real analysis of child mortality. Section 2 was entitled “The essential skills for data analysis” and had chapters on how to visualize data, how to get data, and how to clean data There was information in the chapters that was good for all levels of professionals from beginners to intermediate levels. The explanations of working with Data Frames and JSON data was very helpful. Cleaning data is one of the trickiest parts of data science and there is a chapter on that subject that covers many different data issues including missing data and invalid values. Chapter 4 is “How to Visualize data” and was my favorite chapter because with a few lines of code from the book I was able to produce some really nice charts. I will be able to use these techniques to produce some charts for some ideas I am working on. The explanation for how to interpret a box plot is the best I have ever seen. I also really liked Chapter 8 which is “More skills for data visualization”. This chapter gives more advanced information about creating visualizations in R. Section 3 presents three cases studies and walks the reader through using R to perform analysis for different types of use cases. Section 4 is an introduction to data modeling which goes into simple and multiple regression analysis. The final chapter in the section covers classification models, spending the majority of time on decision trees. The final chapter of the book, Chapter 15 is about R markdown files which can be helpful in producing presentations.