Michael Jarmola has completed
Data Analysis in R, the data.table Way
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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!
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Data.table novice
FreeIntroduction 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.
Section 1 - Introduction50 xpCreate and subset a data.table100 xpGetting to know a data.table100 xpSection 2 - Selecting columns in j50 xpA data.table of a vector?50 xpA non-existing column50 xpSubsetting data.tables100 xpSection 3 - Doing j by group50 xpThe by basics100 xpUsing .N and by100 xpReturn multiple numbers in j100 xp - 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.
Section 4 - Chaining50 xpChaining, the basics100 xpChaining your iris dataset100 xpSection 5 - Subset of Data50 xpProgramming time vs readability100 xpIntroducing .SDcols100 xpMixing it together: lapply, .SD, .SDcols and .N100 xpSection 6 - Using := in j50 xpAdding, updating and removing columns100 xpTo assign or not to assign, that is the question50 xpDeleting a column for a subset of rows50 xpThe functional form100 xpSection 7 - Using set()50 xpReady, set(), go!100 xpThe set() family100 xp - 3
Data.table expert
Discover the potential behind indexing, followed by generating and using keys. The final part focuses on fast ordered joins.
Section 8 - Indexing50 xpSelecting rows the data.table way100 xpRemoving columns and adapting your column names100 xpUnderstanding automatic indexing100 xpSection 9 - Keys50 xpCheck to see if you understood the KEY takeaways50 xpSelecting groups or parts of groups100 xpSection 10 - Rolling joins50 xpRolling joins - part one100 xpRolling joins - part two100 xpRolling joins - final part50 xp
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