working with your data (chapter 2 in the little sas book)

IOWA STATE UNIVERSITYDepartment of Animal Science

Working with Your Data (Chapter 2 in the Little SAS Book)

Animal Science 500Lecture No. 4

September 9, 2010


Working with Your DataTo this point we have identified

1. Many forms which data can stored and ultimately imported into SAS

1. Spreadsheets – Excel, Lotus, Quattro Pro, etc.2. Databases – Access, SQL, others3. Text files – from Word, WordPad, Notepad, others4. Other fileformats

2. Many ways to import our data into SAS1. Import wizard2. Infile statement3. Others

Many options to use with the importing of the data, formatting the input data, etc.


Modifying your Datau Data step

n read and modify datan create a new datasetn performs actions on rows

u Proc stepn use an existing datasetn produce an output/resultsn performs actions on columns


Modifying your Datau Creating and redefining variables is

straightforward in a SAS data stepn variable = expression;

u Examplesn Newvariable = constant;n Newvariable = oldvariable * constant;n Adjusted Backfat, growth rate, loin muscle area =

predetermined equation


Arithmetic Operators

Operation Symbol Example Result+ addition Num + Num

Example: 5 + 3add two numbers together

- subtraction Num - Num Example: 5 – 3 or can use two variables ending wt. – beginning wt.

subtract the value of 5 -3

* multiplication (table note 1)

2*yAlways have to have * cannot use 2(y) or 2y

multiply 2 by the value of Y

/ division var/5or can use variable weight gain / days on test

divide the value of VAR by 5

** can

also use the ^

exponentiation a**2or a^2

raise A to the second power


Comparison Operatorsu Comparison operators set up a comparison, operation,

or calculation with two variables, constants, or expressions within the dataset being used . n If the comparison is true, the result is 1. n If the comparison is false, the result is 0.

u Comparison operators can be expressed as symbols or with their mnemonic equivalents, which are shown in the following table:


Comparison Operators

SymbolMnemonic Equivalent Definition Example

= EQ equal to a=3

^= NE not equal to (table note 1) a ne 3

¬= NE not equal to

~= NE not equal to

> GT greater than num>5

< LT less than num<8 >= GE greater than or equal to

(table note 2)sales>=300

<= LE less than or equal to (table note 3) sales<=100

IN equal to one of a list num in (3, 4, 5)


Logical (Boolean) Operators and Expressions

Symbol Mnemonic Equivalent Example& AND (a>b & c>d)| OR (a>b or c>d)! OR

¦ OR

¬ NOT not(a>b)

ˆ NOT

~ NOT

Logical operators, also called Boolean operators, are usually used in expressions to link sequences of comparisons.


Order of calculationsu The order in which any of the functions follow

standard mathematical rules of precedence.u To overcome this parentheses are used to

override that order.


Modifying your Datau The DROP or KEEP statements

n Used to decrease the number of variablesn Usually not a concern with datasets normally

encounteredn Remember that the variables are dropped or

retained (keep) within the SAS dataset unless you specify otherwise


Modifying your DataData new2; set new;

ADG = ((Finalwt. – Beginningwt) / DaysOnTest);

Drop Beginningwt DaysOnTest;

Proc Means;Run; Quit;


Using IF – THEN Statementsu In cases where we want to assign some

statement to some of your observations but not all.n For example adjustment factors for backfat, loin muscle

area, growth rate that differing by sex of animal

u Called condition – action statementsu IF condition THEN action;


Using IF – THEN Statementsu Example1

n If job='banker' then highsal=1;

u IF condition AND condition THEN action;u Example2u If job='banker' and age>65 then ret_banker=1;u If job eq ‘banker’ and age ge 65 tehn ret_banker=1;


Using the IN Operatoru Using the IN operator makes comparisons and

works similarly to the If – Then statement but gives a bit more flexibility

u IF Model IN (‘Corvette’, ‘Camaro’) Then make = ‘Cheverolet’;n Assumes you have a column or variable titled Modeln Creates new variable or column titled Cheverolet


Using the IN Operatoru Example using animal data. u IF SEX IN (‘gilt’, ‘barrow’) Then adjustedBF = BF +

((actualwt – 250) * (actualbf / (actualwt – constant1)));

u IF SEX IN (‘boar”) Then adjustedBF = BF + ((actualwt – 250) * (actualbf / (actualwt – constant2)));


Using IF – THEN Statementsu A single IF – THEN statement can have

only one actionu Using the key words DO and END then it

is possible to execute more than 1 actionu Example IF condition THEN DO; action; action; END;


Using IF – THEN Statementsu A single IF – THEN statement can have

only one actionu Using the key words DO and END then it

is possible to execute more than 1 actionu Example IF Model = ‘Mustang” THEN DO; Make = ‘Ford’; Size = ‘Compact’; END;


Using IF – THEN Statementsu The AND and OR keywords can be used

to specify multiple conditionsn IF condition AND condition THEN action;

u Examplel IF Model = ‘Mustang’ AND Year < 1975 THEN

Status = ‘Classic’; both conditions must be met to reach the ‘Classic” status

l IF Model = ‘Mustang’ OR Year < 1975 THEN Status = ‘Classic’; only one of the conditions must be met to reach the ‘Classic” status


Using IF – THEN /ELSE Statements

u Using the IF - Then / Else statement is typically used to group observations

u Basic form of statementn IF condition THEN action;

ELSE IF condition THEN action;ELSE IF condition THEN action;

Advantages: When compared to regular IF – THEN statements1. Computationally more efficient as it uses less computer time

because once a condition is satisfied SAS skips the rest of the steps.

2. The ELSE statement is mutually exclusive thus preventing an observation from ending up in more than one group.


The DO – END statementThe DO-END statement is useful if you want to make several

changes or create new variables for a subgroup or under certain conditions.

Note that the DO-loop continues until you end it using END;Example

If sex = ’female’ then do;u AdjustedBF = equation;u AdjustedLMA = equation;u AdjustedDAYS = equation;u End;


The DO – END statementThe DO-END statement is useful if you want to make several

changes or create new variables for a subgroup or under certain conditions.

Note that the DO-loop continues until you end it using END;u Else if sex EQ ’male’ then do;u ...u ...u end;


Using IF – THEN /ELSE Statements

u Example:u IF CowBC . THEN AdjustedCowBC = .;

ELSE IF CowBC ge 9 THEN AdjustedCowBC = 5;ELSE IF CowBC ge 7 and lt 9 THEN AdjustedCowBC = 4;ELSE IF CowBC ge 5 and lt 7 THEN AdjustedCowBC = 3;ELSE IF CowBC ge 3 and lt 5 THEN AdjustedCowBC = 2;ELSE IF CowBC ge 1 and lt 3 THEN AdjustedCowBC = 1;

ELSE IF condition THEN action;


Using IF – THEN /ELSE Statementsu When the condition is true, SAS assigns the stated value

to AdjustedCowBC and then leaves the loop. The last ELSE is a trash-bin: anything that is not covered by the previous conditions is put to missing.

u Look at what gets assigned to the last ELSE statement as it may identify an error in the data set or other problems

u Make sure the condition part includes all possibilities, else you might get missings or hidden errors.

u Examine the log where it will reveal the number of missing values created, but there is no indication for observations that were not covered by your programming!


Subsetting your datau Sometimes researchers or programmers want

to look at only a portion of the data that is collected.

u Can accomplish this using the IF statementu Example only interested in gilts in a dataset

that includes data from boars and barrows.n IF sex = ‘barrow’ THEN delete;n IF sex = ‘boar” THEN delete;


Subsetting your datau Sometimes researchers or programmers want

to look at only a portion of the data that is collected.

u Another way to use the IF statementu Rather than making it an deletion statement,

make an inclusionary statement;u Example only interested in gilts in a dataset

that includes data from boars and barrows.n IF sex = ‘gilt’; this results in the program looking at data

where sex = gilt


Subsetting your dataWhat is the difference when looking at only gilts if the statements IF sex = ‘gilt’; this results in the program looking at data where sex = gilt;IF sex = ‘barrow’ THEN delete; IF sex = ‘boar” THEN delete;

Dataset would include anything coded incorrectly in the dataset other than ‘barrow’ or ‘boar’Using the inclusionary statement (IF sex =‘gilt”), requires that every line of data be examined


The RETAIN Statementsu Use the RETAIN statement when you

want to keep some or all of the variable from a previous DATA step.n The RETAIN variable list; can appear anywhere

in the DATA stepn You can specify an initial value instead of

missing for variables as followsRETAIN variable list initial value;


The Sum Statementsu The Sum statement is used when have a

cumulative total for some variable. Example used in the book;

RETAIN MaxRuns;MaxRuns = MAX (MaxRuns, Runs);RunsToDate + Runs;

Might want to use something similar if you are totaling milk production across the days in lactation or pigs born alive across parity.


Using Arrays in SASu An array is a temporary holding site for a

collection of variables upon which the same operations will be performed. n Arrays provide convenient shortcuts in programming.n An array is a group of variables that is user defined.n The array is user defined in the DATA step.

l All the variables in an array must either be characters or numeric CANNOT mix character and numeric variables in the same array.


Using Arrays in SASu Array name (n) $ (may or may not be included)

variable list.n The number (n) must match the number of variables in

the list.n An array by itself does nothingn You create the array to perform some function that you

want to perform on all array variables (book uses changing missing value from 9 to .


Using Shortcuts for Lists of Variable Namesu Provides you a listing for inputting variables that have

very similar names n Variable1, Variable2, Variable3, Variable4 and so forthn You could use an input statement that includes all of the names –

INPUT Variable1 Variable2 Variable3 Variable4;

n Alternatively you could write itn INPUT Variable1 – Variable4; and all variable will have

been inputted.

working with your data (chapter 2 in the little sas book)

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