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Learn R programming [Video]

This is the code repository for Learn R programming [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

R is a high-level statistical language and is widely used among statisticians and data miners to develop statistical applications. This solution-based video will be your guide, taking you through different programming aspects with R. Beginning with the basics of R programming, this video provides step-by-step resources and time-saving methods to help you solve programming problems efficiently. Starting with the installation of R, each recipe addresses a specific problem with a discussion that explains the solution and offers insight into how it works. You will learn to work with powerful R tools and techniques. You’ll be able to boost your productivity with the most popular R packages and tackle data structures such as matrices, lists, and factors. You’ll see how to create vectors, handle variables, and perform other core functions. You’ll be able to tackle issues with data input/output and will learn to work with strings and dates. Moving forward, we’ll look into more advanced concepts such as metaprogramming with R and functional programming. Finally, you’ll learn to tackle issues while working with databases and data manipulation.

What You Will Learn

  • Write basic R code
  • Get to know the nuts and bolts of writing R in RStudio
  • Discover the basics of variable assignment and expression
  • Get a tour of the most important data structures in R
  • Find out how to create, edit, and subset data structures
  • Get to know a set of techniques for importing data, manipulating data, performing statistical analysis, and producing useful data syntheses

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
This course is for students, data science enthusiasts, and people who are looking for easy and handy solutions to common R problems. This course assumes some previous computer programming experience.

Technical Requirements

This course has the following software requirements:
RStudio

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