Introduction to R: Getting Started
145This is lesson 1 of a 30-part introduction to the R programming language for data analysis and predictive modeling. Link to the code notebooks below:
Intro to R Index: https://www.kaggle.com/hamelg/intro-to-r-index
Intro to R: Getting Started: https://www.kaggle.com/hamelg/intro-to-r-part-1-getting-started
This guide does not assume any prior exposure to R, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn R.
I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can fork and edit each lesson so that you can follow along and run code yourself.
Text Excerpt From Lesson 1:
R is an open source programming language that is popular for statistics and data analysis. R was built by statisticians, so many common statistical operations are built into the base language. R also features powerful and intuitive libraries for plotting and a variety of packages for predictive modeling, making it one of the most popular languages for data science. Essentially every programming kernel you'll find on Kaggle is written in either R or Python.
If you're wondering whether you should start your data science journey by learning R or Python, there's no correct answer. Both languages are used extensively in data science and it a good idea to learn the basics of both. R is great for data exploration, statistics and plotting, as most of the functions you need are built into the language or a part of one or two major packages that are easy to load. This makes it particularly easy to get started doing interesting things with data using R.
Next lesson: https://www.youtube.com/watch?v=x3rtUyr5zvM
Introduction to R Playlist:
https://www.youtube.com/playlist?list=PLiC1doDIe9rDjk9tSOIUZJU4s5NpEyYtE
Other Videos By DataDaft
| 2019-08-09 | Introduction to R: Control Flow |
| 2019-08-07 | Introduction to R: Reading and Writing Data |
| 2019-08-06 | Introduction to R: Factors |
| 2019-08-05 | Introduction to R: Data Frames |
| 2019-07-15 | Introduction to R: Lists |
| 2019-07-12 | Introduction to R: Matrices |
| 2019-07-11 | Introduction to R: Vectors |
| 2019-07-10 | Introduction to R: Variables |
| 2019-07-09 | Introduction to R: Atomic Data Types |
| 2019-07-08 | Introduction to R: R Arithmetic |
| 2019-07-01 | Introduction to R: Getting Started |
| 2019-07-01 | Get the Sum of Each Row in R |
| 2019-07-01 | Get the Sum of Each Column in R |
| 2019-06-30 | How To Apply a Function to Each Column in R |
| 2019-05-22 | How to Create a Data Frame in R |
| 2019-05-22 | How to Subset a Data Frame by a Column in R |
| 2019-05-21 | How to Add a Row To a Data Frame in R |
| 2019-05-21 | How to Add Columns to a Data Frame in R |
| 2019-05-20 | How to Remove a Row From a Data Frame in R |
| 2019-05-16 | Replace NA with 0 in R |
| 2019-05-15 | Count NA in R |