In this final tutorial of our Introduction to dplyr series, we will cover ways to do feature engineering both with dplyr (“mutate” and “transmute”) and base R (“ifelse”). You’ll learn how to impute missing values as well as create new …
We introduce functions that make it easy to find overlapping and distinct values from two different data sources, intersect and setdiff. These two functions let you see the shared and unique elements from different vectors, making it easy to …
We go over some basic functions of dplyr including the mighty group_by and summarize combo that makes dividing up datasets a breeze, as well as arrange, select, and filter that help get the data in a cleaner and more organized …
dplyr is a a great tool to perform data manipulation. It makes your data analysis process a lot more efficient. Even better, it’s fairly simple to learn and start applying immediately to your work! Oftentimes, with just a few elegant …
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