R Data Pre-Processing & Data Management - Shape your Data!
4.2 (111 ratings)
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R Data Pre-Processing & Data Management - Shape your Data!

Learn how to prepare your data for great analytics in R.
4.2 (111 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.
896 students enrolled
Last updated 7/2017
Current price: $12 Original price: $110 Discount: 89% off
3 days left at this price!
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  • 2.5 hours on-demand video
  • 6 Articles
  • 2 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion

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What Will I Learn?
  • 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
View Curriculum
  • 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

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!

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
Compare to Other R Courses
Curriculum For This Course
30 Lectures
2 Lectures 08:58
Data Import and Data Structuring
5 Lectures 27:04
Script: Data import

Importing data and snippets

Using fread to handle big data fast

Choosing the right class for your data

Further R Exercises
Cleaning Your Data
5 Lectures 22:04
Script: Data cleaning

tidyr - How tidy data looks like

Wide to long data format

Splitting columns

Long to wide data format
Querying and Filtering Data with data.table
8 Lectures 51:44
Script: Querying with data.table

What is data.table?

Basic queries

The by paramater for queries


Data.table exercises

Data.table solutions
Using dplyr on one and multiple Datasets
5 Lectures 31:40
Script: dplyr

Single Table Verbs in 'dplyr'

Two Table Verbs - Mutating Joins

Two Table Verbs - Filtering Joins and handling of ID mismatches

Integrate SQL into R
5 Lectures 18:59
Script: Integrate SQL

Get package dbplyr

R to SQL Translator

Set Up a SQLite Database in R
About the Instructor
R-Tutorials Training
4.4 Average rating
5,884 Reviews
63,485 Students
17 Courses
Data Science Education

R-Tutorials is your provider of choice when it comes to analytics training courses! Try it out – our 60,000+ students love it.

We focus on Data Science tutorials. Offering several R courses for every skill level, we are among Udemy's top 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 here to help you boost your career with analytics training – Just learn and enjoy.