← SASnRFirst dot and last dot concept

Introduction

Sometimes we want rows where a group has exactly one record — subjects with a single visit, ages that appear only once, terms reported by only one subject.
In SAS, first.var AND last.var on the same row is the flag combination that marks a group of size one — the row is both the first and the last in its group.
Tidyverse counts group size with mutate(nrows = n()) after group_by(), then filters to nrows == 1.
Base R uses ave(..., FUN = length) to compute the group size per row, then subsets to rows where the size is 1.
This lesson picks ages that appear in exactly one row of CLASS — the ones where the Age group has only a single subject.
After running, inspect the result and confirm each surviving Age value shows up only once in CLASS.

First dot and last dot concept

SAS (Base SAS)+

data CLASS;
 infile datalines dlm='|' dsd missover;
input Name : $8. Sex : $1. Age : best32. Height : best32. Weight : best32.;
label ;
 format ;
 datalines4;
Alfred|M|14|69|112.5
Alice|F|13|56.5|84
Barbara|F|13|65.3|98
Carol|F|14|62.8|102.5
Henry|M|14|63.5|102.5
James|M|12|57.3|83
Jane|F|12|59.8|84.5
Janet|F|15|62.5|112.5
Jeffrey|M|13|62.5|84
John|M|12|59|99.5
Joyce|F|11|51.3|50.5
Judy|F|14|64.3|90
Louise|F|12|56.3|77
Mary|F|15|66.5|112
Philip|M|16|72|150
Robert|M|12|64.8|128
Ronald|M|15|67|133
Thomas|M|11|57.5|85
William|M|15|66.5|112
;;;;
 run;

proc sort data=class;
    by age;
 run;

data only_one_in_group;
     set class;
     by age;
     if first.age and last.age;
 run;

When both first.var and last.var are TRUE for the same row, that row is the only one in its group.
After proc sort data=class; by age;, the DATA step reads CLASS with by age; so the first.age / last.age flags are available.
if first.age and last.age; is a subsetting IF — SAS writes out the row only when the condition is TRUE, which happens only when the Age group has exactly one row.
No output or retain statement is needed; the subsetting IF is all we need to thin the output to singleton groups.
After running, ONLY_ONE_IN_GROUP contains those CLASS rows whose Age appears only once in the sample.
A good sanity check: a frequency count of Age on CLASS should show frequency 1 for exactly the Age values we see in ONLY_ONE_IN_GROUP.

R (tidyverse)+

library(tidyverse) 
class<-tribble(
~Name,~Sex,~Age,~Height,~Weight, 
"Alfred","M",14,69,112.5, 
"Alice","F",13,56.5,84, 
"Barbara","F",13,65.3,98, 
"Carol","F",14,62.8,102.5, 
"Henry","M",14,63.5,102.5, 
"James","M",12,57.3,83,
 "Jane","F",12,59.8,84.5, 
"Janet","F",15,62.5,112.5, 
"Jeffrey","M",13,62.5,84, 
"John","M",12,59,99.5, 
"Joyce","F",11,51.3,50.5, 
"Judy","F",14,64.3,90,
 "Louise","F",12,56.3,77, 
"Mary","F",15,66.5,112, 
"Philip","M",16,72,150, 
"Robert","M",12,64.8,128, 
"Ronald","M",15,67,133, 
"Thomas","M",11,57.5,85, 
"William","M",15,66.5,112, 
) 
only_one_in_group<-class %>% 
group_by(age) %>% 
mutate(nrows=n()) %>% 
filter(nrows==1)

In tidyverse, "group of size one" is expressed with a grouped count followed by a filter.
group_by(age) %>% mutate(nrows = n()) %>% filter(nrows == 1) first attaches the group size to every row, then keeps only rows where the size equals 1.
n() inside a grouped mutate() returns the number of rows in the current group — the direct tidyverse equivalent of counting with PROC FREQ.
Because mutate() keeps the row count, the resulting tibble shows the same columns as the input, with the nrows helper column added.
A small cleanup step is to drop the helper column with select(-nrows) or to use filter(n() == 1) directly without creating the helper in the first place.
We run and compare the survivors against the SAS ONLY_ONE_IN_GROUP dataset — the same rows should come through in both languages.

Happy learning!

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Introduction

First dot and last dot concept