← SASnRCreate Sample Data

Introduction

Before we can run any analysis, we need data in memory. In a teaching setting, the quickest way is to build a tiny dataset inline inside the program itself — no external files, no study database.
SAS programmers typically do this with a DATA step plus datalines. R offers two natural alternatives: tribble() for a readable row-wise form and data.frame() for a column-wise form.
This lesson shows the same 3-row CLASS dataset built in each environment so we can compare the syntax side by side.
After running any of the three, we should have a table with columns Name, Sex, Age, Height and Weight, and three observations representing Alfred, Alice and Barbara.

Create Sample Data

SAS (Base SAS)+

data CLASS;
  infile datalines dlm='|' dsd missover;
  input Name : $8. Sex : $1. Age : best32. Height : best32. Weight : best32.;
  datalines;
  Alfred|M|14|69|112.5
  Alice|F|13|56.5|84
  Barbara|F|13|65.3|98
;
run;

To create an inline dataset in SAS, we use a DATA step followed by infile datalines and an input statement describing each variable.
dlm='|' tells SAS the values are pipe-separated. dsd activates delimiter-sensitive data handling so empty fields are treated as missing. missover prevents SAS from reading past the end of a short line.
The input statement declares each variable with its informat — $8. for an 8-character name, $1. for sex, best32. for flexible numeric reads.
After the datalines; statement we list the raw rows, terminated by a bare semicolon.
run; executes the step and writes the resulting CLASS dataset to the WORK library.

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
)

To build a small dataset inline in tidyverse, we use tribble() — a row-wise constructor that reads top-to-bottom the same way we would write it on paper.
Column names come first, each prefixed with ~ to mark them as tibble variables.
Each subsequent line of values becomes one observation. Commas separate fields within a row; the structure is far more scannable than the equivalent data.frame() call.
tribble() is especially handy for writing unit tests and teaching examples where we care about readability more than raw performance.
The result is a tibble — tidyverse’s drop-in replacement for a data frame, with nicer printing and stricter subset behaviour.

Happy learning!

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Introduction

Create Sample Data