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Learning R Programming

Learning R Programming

By : Ren
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Learning R Programming

Learning R Programming

By: Ren

Overview of this book

R is a high-level functional language and one of the must-know tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution - an easy and practical way to learn R and develop a broad and consistent understanding of the language. Through hands-on examples you'll discover powerful R tools, and R best practices that will give you a deeper understanding of working with data. You'll get to grips with R's data structures and data processing techniques, as well as the most popular R packages to boost your productivity from the offset. Start with the basics of R, then dive deep into the programming techniques and paradigms to make your R code excel. Advance quickly to a deeper understanding of R's behavior as you learn common tasks including data analysis, databases, web scraping, high performance computing, and writing documents. By the end of the book, you'll be a confident R programmer adept at solving problems with the right techniques.
Table of Contents (16 chapters)
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Understanding code performance issues

From the very beginning, R is designed for statistical computing and data visualization and is widely used by academia and industry. For most data analysis purposes, correctness is more important than performance. In other words, getting a correct result in 1 minute should be better than getting an incorrect one in 20 seconds. A result that is three times faster is not automatically three times more valid than a slow but correct result. Therefore, performance should not be a concern before you are sure about the correctness of your code.

Let's assume that you are 100 percent sure that your code is correct but it runs a bit slowly. Now, is it necessary for you to optimize the code so that it can run faster. Well, it depends. Before making a decision, it is helpful to divide the time of problem solving into three parts: time of development, execution, and future maintenance.

Suppose we have been working on a problem for an hour. Since we didn&apos...

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Learning R Programming
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