Useful dplyr Functions

Kevin Feasel

2017-07-12

R

S. Richter-Walsh explains seven important dplyr functions with plenty of examples:

There are many useful functions contained within the dplyr package. This post does not attempt to cover them all but does look at the major functions that are commonly used in data manipulation tasks. These are:

select()
filter()
mutate()
group_by()
summarise()
arrange()
join()

The data used in this post are taken from the UCI Machine Learning Repository and contain census information from 1994 for the USA. The dataset can be used for classification of income class in a machine learning setting and can be obtained here.

That’s probably the bare minimum you should know about dplyr, but knowing just these seven can make data analysis in R much easier.

Related Posts

The Lesser-Known Apply Functions In R

Andrew Treadway covers a few of the lesser-known apply functions in R: rapply Let’s start with rapply. This function has a couple of different purposes. One is to recursively apply a function to a list. We’ll get to that in a moment. The other use of rapply is to a apply a function to only those elements in […]

Read More

Controlling Azure Services In R With AzureR

Hong Ooi announces a new set of packages called AzureR: As background, some of you may remember the AzureSMR package, which was written a few years back as an R interface to Azure. AzureSMR was very successful and gained a significant number of users, but it was never meant to be maintainable in the long term. As […]

Read More

Categories

July 2017
MTWTFSS
« Jun Aug »
 12
3456789
10111213141516
17181920212223
24252627282930
31