YoVDO

Introduction to R

Offered By: DataCamp

Tags

Data Science Courses Statistics & Probability Courses Data Analysis Courses R Programming Courses Vectors Courses Matrices Courses

Course Description

Overview

Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

In this introduction to R course, you'll master the basics of this widely used open source language—including vectors, factors, lists, and data frames. With the coding skills you'll gain in this course, you'll be ready to undertake your own data analysis in R. There are millions of R users worldwide, cementing it as a leading programming language in statistics and data science. Begin your coding journey in one of DataCamp's most popular courses today!

Syllabus

  • Intro to basics
    • Take your first steps with R. In this chapter, you will learn how to use the console as a calculator and how to assign variables. You will also get to know the basic data types in R. Let's get started.
  • Vectors
    • We take you on a trip to Vegas, where you will learn how to analyze your gambling results using vectors in R. After completing this chapter, you will be able to create vectors in R, name them, select elements from them, and compare different vectors.
  • Matrices
    • In this chapter, you will learn how to work with matrices in R. By the end of the chapter, you will be able to create matrices and understand how to do basic computations with them. You will analyze the box office numbers of the Star Wars movies and learn how to use matrices in R. May the force be with you!
  • Factors
    • Data often falls into a limited number of categories. For example, human hair color can be categorized as black, brown, blond, red, grey, or white—and perhaps a few more options for people who color their hair. In R, categorical data is stored in factors. Factors are very important in data analysis, so start learning how to create, subset, and compare them now.
  • Data frames
    • Most datasets you will be working with will be stored as data frames. By the end of this chapter, you will be able to create a data frame, select interesting parts of a data frame, and order a data frame according to certain variables.
  • Lists
    • As opposed to vectors, lists can hold components of different types, just as your to-do lists can contain different categories of tasks. This chapter will teach you how to create, name, and subset these lists.

Related Courses

Address Business Issues with Data Science
CertNexus via Coursera
Advanced Clinical Data Science
University of Colorado System via Coursera
Advanced Data Science Capstone
IBM via Coursera
Advanced Data Science with IBM
IBM via Coursera
Advanced Deep Learning Methods for Healthcare
University of Illinois at Urbana-Champaign via Coursera