← SASnRSorting observations

Introduction

Arranging rows into a meaningful order is a common first step before any downstream summary or merge.
Typical reasons: sort by subject and visit, sort descending by date, or order a frequency output by count.
SAS uses proc sort with a by statement; tidyverse uses arrange() from dplyr; base R uses order() on the data frame.
This lesson sorts CLASS by Age ascending, then Height descending, so we can compare the three syntaxes side by side.
After running, the first row should be the youngest subject; within ties on Age, the taller subject should come first.

Sorting observations

SAS (Base SAS)+

R (tidyverse)+

library(tidyverse)

class<-tribble(
~Name,~Sex,~Age,~Height,~Weight,
"Alfred","M",14,69,112.5,
"Henry","M",14,63.5,102.5,
"James","M",12,57.3,83,
)

sorted<-arrange(class,Age,desc(Height))

To sort a tibble in tidyverse, we use arrange() from dplyr.
arrange(class, Age, desc(Height)) sorts by Age ascending, then by Height descending within ties on Age.
Columns default to ascending; wrap any column in desc() to flip it — the dplyr equivalent of the SAS descending keyword.
arrange() returns a new tibble and leaves the original data frame untouched, similar to using out= in SAS.
Missing values go to the bottom regardless of sort direction — see lesson 1901 for explicit control over NA placement.
We run and confirm the row count is unchanged and the sort keys move in the expected directions.

Happy learning!

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Introduction

Sorting observations