Data Analysis in R, the data.table Way

Master core concepts in data manipulation such as subsetting, updating, indexing and joining your data using data.table.
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4 Hours10 Videos37 Exercises60,269 Learners
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Course Description

The R data.table package is rapidly making its name as the number one choice for handling large datasets in R. This online data.table tutorial will bring you from data.table novice to expert in no time. Once you are introduced to the general form of a data.table query, you will learn the techniques to subset your data.table, how to update by reference and how you can use data.table’s set()-family in your workflow. The course finishes with more complex concepts such as indexing, keys and fast ordered joins. Upon completion of the course, you will be able to use data.table in R for a more efficient manipulation and analysis process. Enjoy!

  1. 1

    Data.table novice

    Free
    Introduction on what exactly a data.table is, how it differs from the traditional data.frame in R, and understanding the general form of a data.table query.
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  2. 2

    Data.table yeoman

    Learn how to do multiple operations on the same data.table in one single statement, how to easily take a subset of your data, update by reference, and work with the data.table set()-family.
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  3. 3

    Data.table expert

    Discover the potential behind indexing, followed by generating and using keys. The final part focuses on fast ordered joins.
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Prerequisites
Introduction to RIntermediate R
Matt Dowle Headshot

Matt Dowle

Author of data.table
Matt Dowle is the main author of the data.table package. Matt has worked for some of the world’s largest financial organizations and has been programming in R for over a decade.
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Arun Srinivasan Headshot

Arun Srinivasan

R's data.table co-developer
Arun Srinivasan is originally from Tamilnadu, India. He holds a Bachelors degree in Electronics engineering and a Masters degree in Bioinformatics. He started using R in 2010 and has contributed to R's data.table package since late 2013. He currently lives in London, where he works as a developer and analyst in Finance. He has a passion for developing tools and algorithms facilitating analyses on large data.
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Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

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Harvard Business School

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Decision Science Analytics, USAA