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Together with the key people behind the data.table package, Matt Dowle and Arun Srinivasan, DataCamp developed a brand new interactive course to bring your data analysis skillset up to date with the essentials of the powerful data.table package. Learn more on the data.table tutorial… The popularity of the data.table package is increasing and with good reason. Not only is the number of package downloads rising rapidly, but data.table is also talk of the R town given the numerous presentations of Matt and Arun at conferences such as useR!2014, EARL, R/Insurance and R/Finance.Data.table allows you to reduce your programming time as well as your computing time considerably, and it is especially useful if you often find yourself working with large datasets. For example, to read in a 20GB .csv file with 200 million rows and 16 columns, data.table only needs 8 minutes thanks to the Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
fread()
function. This is instead of the hours it would take you with the read.csv()
function. Once you understand its concepts and principles, the speed and simplicity of the package are astonishing!
On the data.table tutorial
However, to get the most out of data.table’s functionalities, you first have to overcome its learning curve: even though the syntax is not extremely difficult, it does take some practice to fully grasp it so its built-in functionalities can make your life easier. This is exactly why DataCamp has made an interactive online course on the data.table package for R and it has done so in collaboration with the key people behind it, namely Matt Dowle, main author, and Arun Srinivasan, co-author and major contributor. The data.table tutorial, which is unique as it is the only one of its kind, is called Data Analysis: the data.table way. It is designed to help you get started with the essentials of the data.table package. Among other things, you will learn all there is to know about operations such as selection and grouping inDT[i, j, by]
, and intermediate topics like chaining, setting keys and the different join types.To leave a comment for the author, please follow the link and comment on their blog: DataCamp Blog.
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