← SASnRAppending datasets

Introduction

Appending datasets means stacking rows — taking two tables with the same (or compatible) column structure and producing one table with all the rows combined.
A typical clinical use case is combining data from multiple studies or sites into a single analysis-ready dataset.
SAS offers PROC APPEND or a DATA step with multiple SET datasets. Tidyverse provides bind_rows(). Base R provides rbind().
This lesson appends a small second dataset to the original CLASS dataset, producing a combined table.
After running, the combined dataset has all rows from both inputs.

Appending datasets

SAS (Base SAS)+

data MALES;
 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
Henry|M|14|63.5|102.5
James|M|12|57.3|83
;;;;
 run;

data FEMALES;
 infile datalines dlm='|' dsd missover;
input Name : $8. Sex : $1. Age : best32. Height : best32. Weight : best32.;
label ;
 format ;
 datalines4;
Alice|F|13|56.5|84
Barbara|F|13|65.3|98
Carol|F|14|62.8|102.5
;;;;
 run;

data class;
     set males females;
 run;

To append rows in SAS, the classic approach is a DATA step with multiple datasets on the SET statement: set class class2;.
SAS reads every observation from class first, then every observation from class2, into the output dataset.
Variables with the same name and type are merged automatically. Variables that exist in only one side get missing values for the other side’s rows.
An alternative is PROC APPEND base=class data=class2; — it writes class2 onto the end of class in place, without creating a new dataset. Useful for very large data where we do not want to duplicate.
After running, the output has all rows from both inputs and every column from either side.

R (tidyverse)+

males <- 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,
)

 

females <- tribble( ~Name,~Sex,~Age,~Height,~Weight,
"Alice","F",13,56.5,84,
"Barbara","F",13,65.3,98,
"Carol","F",14,62.8,102.5, 
)

class <- bind_rows(males,females)

In tidyverse, we append rows with bind_rows().
bind_rows(class, class2) returns a new tibble with every row from both inputs stacked top-to-bottom.
Like the SAS DATA step, bind_rows() matches columns by name. Columns that exist in only one side get NA on the other side’s rows.
We can supply a named id column to tag where each row came from: bind_rows(study_a = class, study_b = class2, .id = "source") adds a source column with "study_a" or "study_b".
After running, the combined tibble has rows = rows_of_class + rows_of_class2.

Happy learning!

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Introduction

Appending datasets