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What is the word meaning of 'Appending'?

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attach
add (something) to the end of a written document.

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Common scenarios where appending (of datasets) is required in SAS?

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Combine the records of students of different classes when a separate dataset is present for each class
Combine the recods of male and female students when male and female records are present in different datasets
Combine the records of screen failures and treated subjects when they are present in different datasets
Combine the records of inclusion criteria and exclusion criteria not met by subjects when they are present in different datasets
Combine the prior medications data and concomitant medications data of subjects when they are present in different datasets
Combine all the input datasets available to check the latest available date for a subject across all datasets

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What does 'SET statement' of SAS data step do?

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By definition, set statement is used for reading observations from one or more datasets
When only one dataset name is provided on the set statement, it reads all the observations from the input dataset unless otherwise specified and creates a new dataset (or overwrites existing dataset when same dataset name is provided in the data statement)
As specified in the first point, set statement can be used to read observations from more than dataset in a single data step
We use this ability to read observations from multiple datasets for appending observations from one dataset to another dataset
To append datasets, we need to specify the names of the input datasets separated by space on the set statement
When appending, SAS reads all the observations from first input dataset and then starts reading the observations from the nex input dataset. That is, in the output dataset we will see the observations from first dataset first followed the observations from second input dataset and so on

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Create some example datasets

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data males females;
     set sashelp.class;
     if sex="M" then output males;
     if sex="F" then output females;
  run;
   
  data preteen teen;
     set sashelp.class;
     if age lt 13 then output preteen;
     if age ge 13 then output teen;
  run;
   
  data sedan sports othercars;
     set sashelp.cars;
     if type="Sedan" then output sedan;
     else if type="Sports" then output sports;
     else output othercars;
  run;

219995  data males females;
  219996     set sashelp.class;
  219997     if sex="M" then output males;
  219998     if sex="F" then output females;
  219999  run;
   
  NOTE: There were 19 observations read from the data set SASHELP.CLASS.
  NOTE: The data set WORK.MALES has 10 observations and 5 variables.
  NOTE: The data set WORK.FEMALES has 9 observations and 5 variables.
  NOTE: DATA statement used (Total process time):
        real time           0.03 seconds
        cpu time            0.03 seconds
   
   
  220000
  220001  data preteen teen;
  220002     set sashelp.class;
  220003     if age lt 13 then output preteen;
  220004     if age ge 13 then output teen;
  220005  run;
   
  NOTE: There were 19 observations read from the data set SASHELP.CLASS.
  NOTE: The data set WORK.PRETEEN has 7 observations and 5 variables.
  NOTE: The data set WORK.TEEN has 12 observations and 5 variables.
  NOTE: DATA statement used (Total process time):
        real time           0.03 seconds
        cpu time            0.01 seconds
   
   
  220006
  220007  data sedan sports othercars;
  220008     set sashelp.cars;
  220009     if type="Sedan" then output sedan;
  220010     else if type="Sports" then output sports;
  220011     else output othercars;
  220012  run;
   
  NOTE: There were 428 observations read from the data set SASHELP.CARS.
  NOTE: The data set WORK.SEDAN has 262 observations and 15 variables.
  NOTE: The data set WORK.SPORTS has 49 observations and 15 variables.
  NOTE: The data set WORK.OTHERCARS has 117 observations and 15 variables.
  NOTE: DATA statement used (Total process time):
        real time           0.03 seconds
        cpu time            0.01 seconds

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Combining input datasets having same attributes using SET statement

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When appending datasets with set statement, SAS reads all variables and observations from the input datasets

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Create a dataset named m_and_f by appending males and females datasets using set statement

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We need to specify the name of the output dataset 'm_and_f' on the dataset, to hold the combined variables and observations
We need to specify the names of the input datasets (males and females) on the set statement separated by a space in between.
Notice in the output dataset, all 10 male sudent records are seen first(observations from males dataset) followed by the 9 observations from females dataset

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data m_and_f;
     set males females;
  run;

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Create a dataset named cars1 by appending sedan and sports datasets using SET statement

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data cars1;
     set sedan sports;
  run;

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Create a dataset named allcars by appending cars1 and othercars datasets using SET statement

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data allcars;
     set othercars cars1;
  run;

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Create a dataset named allcars2 by appending sedan,sports and othercars datasets using SET statement

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Recreating input datasets

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data sedan sports othercars;
     set sashelp.cars;
     if type="Sedan" then output sedan;
     else if type="Sports" then output sports;
     else output othercars;
  run;

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Notice that we are appending three datasets at a time

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  data allcars2;
     set sedan sports allcars;
  run;