R Data Pre-Processing & Data Management - Shape your Data!

Learn how to prepare your data for great analytics in R.
4.6 (54 ratings)
Instead of using a simple lifetime average, Udemy calculates a
course's star rating by considering a number of different factors
such as the number of ratings, the age of ratings, and the
likelihood of fraudulent ratings.
529 students enrolled
Sale Ends Today!
86% off
Take This Course
  • Lectures 29
  • Length 2.5 hours
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
Wishlisted Wishlist

How taking a course works


Find online courses made by experts from around the world.


Take your courses with you and learn anywhere, anytime.


Learn and practice real-world skills and achieve your goals.

About This Course

Published 5/2016 English

Course Description

Let’s get your data in shape!

Data Pre-Processing is the very first step in data analytics. You cannot escape it, it is too important. Unfortunately this topic is widely overlooked and information is hard to find.

With this course I will change this!

Data Pre-Processing as taught in this course has the following steps:

1.       Data Import: this might sound trivial but if you consider all the different data formats out there you can imagine that this can be confusing. In the course we will take a look at a standard way of importing csv files, we will learn about the very fast fread method and I will show you what you can do if you have more exotic file formats to handle.

2.       Selecting the object class: a standard data.frame might be fine for easy standard tasks, but there are more advanced classes out there like the data.table. Especially with those huge datasets nowadays, a data.frame might not do it anymore. Alternatives will be demonstrated in this course.

3.       Getting your data in a tidy form: a tidy dataset has 1 row for each observation and 1 column for each variable. This might sound trivial, but in your daily work you will find instances where this simple rule is not followed. Often times you will not even notice that the dataset is not tidy in its layout. We will learn how tidyr can help you in getting your data into a clean and tidy format.

4.       Querying and filtering: when you have a huge dataset you need to filter for the desired parameters. We will learn about the combination of parameters and implementation of advanced filtering methods. Especially data.table has proven effective for that sort of querying on huge datasets, therefore we will focus on this package in the querying section.

5.       Data joins: when your data is spread over 2 different tables but you want to join them together based on given criteria, you will need joins for that. There are several methods of data joins in R, but here we will take a look at dplyr and the 2 table verbs which are such a great tool to work with 2 tables at the same time.

6.       Integrating and interacting with SQL: R is great at interacting with SQL. And SQL is of course the leading database language, which you will have to learn sooner or later as a data scientist. I will show you how to use SQL code within R and there is even a R to SQL translator for standard R code. And we will set up a SQLite database from within R. 

How do you best prepare yourself for this course?

You only need a basic knowledge of R to fully benefit from this course. Once you know the basics of RStudio and R you are ready to follow along with the course material. Of course you will also get the R scripts which makes it even easier.

The screencasts are made in RStudio so you should get this program on top of R. Add on packages required are listed in the course.

Again, if you want to make sure that you have proper data with a tidy format, take a look at this course. It will make your analytics with R much easier!

What are the requirements?

  • Computer with R and RStudio ready to use
  • You should have basic R / RStudio knowledge
  • Required add on packages will be listed in the course orientation video

What am I going to get from this course?

  • import data into R in several ways while also beeing able to identify a suitable import tool
  • select and implement a proper object class (data.frame, data.table, data_frame)
  • convert your data into (and understand) a tidy data format
  • filter and query your data based on a wide range of parameters
  • join 2 data tables together with dplyr 2 table verb syntax
  • use SQL code within R
  • translate basic R into SQL

Who is the target audience?

  • Data pre-processing is a crucial step of data related work - therefore this course is intended for all R users

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.


Section 1: Introduction
Section 2: Data Import and Data Structuring
Script: Data import
Importing data and snippets
Using fread to handle big data fast
Choosing the right class for your data
Further R Exercises
Section 3: Cleaning Your Data
Script: Data cleaning
tidyr - How tidy data looks like
Wide to long data format
Splitting columns
Long to wide data format
Section 4: Querying and Filtering Data with data.table
Script: Querying with data.table
What is data.table?
Basic queries
Queries at column level
The by paramater for queries
Data.table exercises
Data.table solutions
Section 5: Using dplyr on one and multiple Datasets
Script: dplyr
Single Table Verbs in 'dplyr'
Two Table Verbs - Mutating Joins
Two Table Verbs - Filtering Joins and handling of ID mismatches
Two Table Verbs - Set Operations
Section 6: Integrate SQL into R
Script: Integrate SQL
R to SQL Translator
Using SQL within R
Set Up a SQLite Database in R

Students Who Viewed This Course Also Viewed

  • Loading
  • Loading
  • Loading

Instructor Biography

R-Tutorials Training, Data Science Education

R-Tutorials is your provider of choice when it comes to analytics training courses! Try it out – our 30,000+ students love it.

We focus on Data Science tutorials. Offering several R courses for every skill level, we are Udemy's number one R training provider. On top of that courses on Tableau, Excel and a Data Science career guide are available.

All of our courses contain exercises to give you the opportunity to try out the material on your own. You will also get downloadable script pdfs to recap the lessons.

The courses are taught by our main instructor Martin – trained biostatistician and enthusiastic data scientist / R user.

Should you have any questions, you are invited to check out our website, you can open a discussion in the course or you can simply drop us a pm.

We are there to help you boost your career with analytics training – Just learn and enjoy.

Ready to start learning?
Take This Course