logging in or signing up SAS (Statistical Analysis Software) kirtikrushna Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT lite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: Embed: Flash iPad Copy Does not support media & animations WordPress Embed Customize Embed URL: Copy Thumbnail: Copy The presentation is successfully added In Your Favorites. Views: 1736 Category: Science & Tech.. License: Some Rights Reserved Like it (3) Dislike it (0) Added: March 23, 2011 This Presentation is Public Favorites: 2 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Slide 1: SAS (Statistical Analysis System) By: KirtikrushnaSlide 2: SAS (Statistical Analysis System) It was developed by James Good knight. 1970-It was package 1980-Language 1990-SoftwareSlide 3: SAS Technical Techno Functional Functional | | | SAS/BASE SAS/Ware house admin SAS/Stat SAS/MACRO’S SAS/ETL Studio SAS/Graph SAS/ACCESS SAS/OLAP SAS/OR SAS/AFSlide 4: In which domains SAS can be used: CLINICAL BANKING INSURANCESlide 5: INTRODUCTION TO THE SAS SYSTEM : SAS is an integrated system of software solutions that enables you to perform the following tasks: data entry, retrieval, and management report writing and graphics design statistical and mathematical analysis business forecasting and decision support applications developmentSlide 6: Base SAS software provides you with essential tools for the basic data-driven tasks that you commonly perform as a programmer:Slide 7: Accessing Data: you can access data that is stored almost anywhere, whether it is in a file on your system, or data that is stored another database system. In almost any format, including raw data, SAS data sets, and files created by other vendors' software.Slide 8: Managing Data : After you have accessed your data, you can use the SAS programming language to manipulate it. Format your data ,create variables (columns), use operators to evaluate data values ,use functions to create and recode data values, subset data, perform conditional processing, merge a wide range of data sources, create, retrieve, and update database information.Slide 9: Analyzing Data and Presenting Information Once your data is in shape, you can use SAS to analyze data and produce reports. Your SAS output can range from a simple listing of a data set to customized reports of complex relationships.Slide 10: Analysis: Base SAS provides powerful data analysis tools . For example, you can produce tables, frequency counts, and cross-tabulation tables create a variety of charts and plots compute a variety of descriptive statistics, including the mean, sum, variance, standard deviation and more compute correlations and other measures of association, as well as multi-way cross-tabulations and inferential statistics.Slide 11: Presentation For reporting and displaying analytical results, SAS gives you an almost limitless number of visually appealing output formats, such as an array of markup languages including HTML4 and XML output that is formatted for a high-resolution printer, such PostScript, PDF, and PCL files RTF color graphs that you can make interactive using ActiveX controls or Java applets.Slide 12: SAS WINDOW ENVIRONMENT Five windows in SAS 1.Editor window 2.Output window. 3.Log window 4.Result window 5.Explorer window 1.Editor window : Editor window contains the list of programs which has an extension of .SAS We can type any no of programs in editor window We can execute all programs at a time or individuallySlide 13: 2.OUT PUT window Results of program will be displayed in output window which has an extension of .LIST 3.LOG WINDOW Suppose if there are any errors or warnings in the program those messages will be displayed in log window It displays the licensed agreement of SAS Version no of variables , no of observations 4.Result window: It displays result of all the programs in editor window No extension for result window 5.Explorer window Contains Libraries and MycomputerSlide 14: SAS LANGUAGE : The SAS language consists of statements, expressions, options, formats, and functions similar to those of many other programming languages. In SAS, you use these elements within one of two groups of SAS statements: DATA steps PROC stepsSlide 15: DATA STEP: A DATA step consists of a group of statements in the SAS language that can read data from external files write data to external files read SAS data sets and data views create SAS data sets and data views. Create multiple SAS data sets in one DATA STEP. Combine existing data sets Creating accumulating totals Manipulate numeric and character valuesSlide 16: Syntax: DATA <DATA Set Name> INPUT <var1><var2>….<varn>; CARDS; Data values ; RUN;Slide 17: EG: data temp; input name $ no; datalines; hari 102 ravi 104 ganesh 105 kiran 109 ; run;Slide 18: SAS DATA SETS: A SAS data set consists of the following: -descriptor information -data values. The descriptor information describes the contents of the SAS data set to SAS. The data values are data that has been collected or calculated. They are organized into rows, called observations, and columns, called variables. An observation is a collection of data values that usually relate to a single object. A variable is the set of data values that describe a given characteristic.Slide 19: SAS VARIABLES AND OBSERVATIONS The below figure shows a SAS data set. The data describes participants in a 16-week weight program at a health and fitness club. The data for each participant includes an identification number, name, team name, and weight at the beginning and end of the program.Slide 20: PROC STEP: Once your data is accessible as a SAS data set, you can analyze the data and write reports by using a set of tools known as SAS procedures. A group of procedure statements is called a PROC step . SAS procedures analyze data in SAS data sets to produce statistics, tables, reports, charts, and plots, to create SQL queries, and to perform other analyses and operations on your data. They also provide ways to manage and print SAS files.Slide 21: PROCEDURE STEP BLOCK Syntax: Proc <Procedure name>; Statement 1 Statement 2 . . . Statement n ; Run;Slide 22: EG : proc print data=temp; Run; proc sort data=temp out=samp; by name; run;Slide 23: Data Types in SAS System 1)Numerical Data(0-9) 2)Character Data (A-Z) SAS System by default reads both numeric and character data as numeric only To read character data Use $ symbol. The no of variables in SAS System is up to 32767 characters SAS Reads Data values observation by observation The no of observations in SAS Data set depends on system configuration or hard disk space. In SAS data set for missing value in output it shows a period(.) for missing value and “blank space “ for character value.Slide 24: Different Data bases : Best db storage: Text Excel Access DB2 Oracle Tera DataSlide 25: LIBRARIES : There are 2 ways of creating libraries. 1.Menu driven 2.Programming coding 1.Menu driven Explorer | Right click | NewSlide 26: 2.Through programming Editor window LIBNAME <Name of library> <path>; LIBNAME Hari “D:\Ganesh”; Example: To delete Library: Libname Guru clear;Slide 27: RULES FOR SAS STATEMENTS: There are only a few rules for writing SAS statements: _ SAS statements end with a semicolon. _ You can enter SAS statements in lowercase, uppercase, or a mixture of the two. _ You can begin SAS statements in any column of a line and write several statements on the same line. _ You can begin a statement on one line and continue it on another line, but you cannot split a word between two lines.Slide 28: RULES FOR MOST SAS NAMES: SAS names are used for SAS data set names, variable names, and other items. The following rules apply: _ A SAS name can contain from one to 32 characters. _ The first character must be a letter or an underscore (_). _ Subsequent characters must be letters, numbers, or underscores. _ Blanks cannot appear in SAS names.Slide 29: DATA STEP PROCESSING: The DATA step is one of the basic building blocks of SAS programming. It creates the data sets that are used in a SAS program’s analysis and reporting procedures.Slide 30: OVERVIEW OF THE DATA STEP: The DATA step consists of a group of SAS statements that begins with a DATA statement. The DATA statement begins the process of building a SAS data set and names the data set. The statements that make up the DATA step are compiled, and the syntax is checked. If the syntax is correct, then the statements are executed. In its simplest form, the DATA step is a loop with an automatic output and return action.Slide 31: DURING THE COMPILE PHASE: When you submit a DATA step for execution, SAS checks the syntax of the SAS statements and compiles them, that is, automatically translates the statements into machine code. SAS further processes the code, and creates the following two items: INPUT BUFFER PROGRAM DATA VECTOR:Slide 32: INPUT BUFFER: Input buffer is a logical area in memory into which SAS reads each record of raw data when SAS executes an INPUT statement. PROGRAM DATA VECTOR (PDV): Is a logical area in memory where SAS builds a data set, one observation at a time. When a program executes, SAS reads data values from the input buffer or creates them by executing SAS language statements. The data values are assigned to the appropriate variables in the program data vector. From here, SAS writes the values to a SAS data set as a single observation.Slide 33: The PDV contain two automatic variables: 1). _N_ It gives information about variables and observations 2). _ERROR_ classified as 2 types: If _error_=0 means no error in program ii) _error_=1 means there are errors in program.Slide 34: Creating the Input Buffer and the Program Data Vector: When DATA step statements are compiled, SAS determines whether to create an input buffer. If the input file contains raw data (as in the example above), SAS creates an input buffer to hold the data before moving the data to the program data vector (PDV).Slide 35: data total_points (drop=TeamName); input TeamName $ ParticipantName $ Event1 Event2 Event3; TeamTotal + (Event1 + Event2 + Event3); datalines; Knights Sue 6 8 8 Cardinals Jane 9 7 8 Knights John 7 7 7 Knights Lisa 8 9 9 Knights Fran 7 6 6 Knights Walter 9 8 10 ; run;Slide 36: The following figure shows the Input Buffer and the program data vector after DATA step compilation.Slide 37: Position of the Pointer in the Input Buffer Before SAS Reads Data The INPUT statement then reads data values from the record in the input buffer and writes them to the PDV where they become variable values . The following figure shows both the position of the pointer in the input buffer, and the values in the PDV after SAS reads the first record.Slide 39: Program Data Vector with Computed Value of the Sum StatementSlide 40: Writing an Observation to the SAS Data Set The First Observation in Data Set TOTAL_POINTS Output SAS Data Set TOTAL_POINTS: 1st observationSlide 41: SAS then returns to the DATA statement to begin the next iteration. SAS resets the values in the PDV in the following way: The values of variables created by the INPUT statement are set to missing. The value created by the Sum statement is automatically retained. The value of the automatic variable _N_ is incremented by 1, and the value of _ERROR_ is reset to 0.Slide 42: Compilation: Checks code for errors Translate code to machine code Establishes an area of memory called input buffer if reading raw data Establishes an area of memory called the program Data Vector Assign required attributes to variables Creates the descriptor portion of the new data set.Slide 43: Execution: During the execution phase, SAS Initializes the PDV to missing Reads data values in to PDV Carries out assignment statement and conditional processing Writes the observation in the PDV to the output SAS data set at the end of the data step Returns to the top of the Data step Initialize any variable that are not read from SAS data sets to missing Repeat the processSlide 44: Each time the DATA statement executes, a new iteration of the DATA step begins, and the _N_ automatic variable is incremented by 1. As SAS continues to read records, the value in TeamTotal grows larger as more participant scores are added to the variable. _N_ is incremented at the beginning of each iteration of the DATA step. This process continues until SAS reaches the end of the input file. The DATA step stops executing after it processes the last input record.Slide 45: Word Scanner Compiler Input stack Data temp; Input name $ no; Cards; Hari 101 ; %let list=name; proc print data=temp; var &list; run;Slide 46: Input stack ; Input name $ no; Cards; Hari 101 ; %let list=name; proc print data=temp; var &list; run; Data temp compiler Word scannerSlide 47: “The process that SAS uses to extract words and symbols from the input stack to word scanner is called tokenization .” Tokenization is performed by a component of SAS called the word scanner. The word scanner starts at the first character in the input stack and examines each character in turn. Literal a string of characters enclosed in quotation marks. Number digits, date values, time values, and hexadecimal numbers. Name a string of characters beginning with an underscore or letter. Special any character or group of characters that have special meaning to SAS. Examples of special characters include: * / + - ** ; $ ( ) . & % =Slide 48: What Are the SAS Language Elements? Data set options Informats and formats Functions Statements SAS system optionsSlide 49: Definition of Data Set Option: Data set options specify actions that apply only to the SAS data set with which they appear. They enable you to perform operations such as these: Renaming variables Selecting only the first or last n observations for processing Dropping variables from processing or from the output data set Specifying a password for a data set.Slide 50: Syntax for Data Set Options Specify a data set option in parentheses after a SAS data set name. To specify several data set options, separate them with spaces. ( option-1 = value-1 <... option-n = value-n >) These examples show data set options in SAS statements: data scores (keep=team game1 game2 game3);Slide 51: data points (Keep=Event1 Event2); input TName $ PName $ Event1 Event2 ; datalines; Knights Sue 6 8 Cardinals Jane 9 7 Knights John 7 7 Knights Lisa 8 9 ; run;Slide 52: Formats and Informats De.nition of a Format A format is an instruction that SAS uses to write data values. Syntax of a Format SAS formats have the following form: <$> format < w >.< d > Here is an explanation of the syntax: $ indicates a character format; its absence indicates a numeric format. format names the format.Slide 53: w specifies the format width, which for most formats is the number of columns in the output data. d specifies an optional decimal scaling factor in the numeric formats. data temp; amount=1145.32; put amount dollar10.2; run; The DOLLAR w . d format in the PUT statement produces this result: $1,145.32Slide 54: Informats De.nition of an Informat An informat is an instruction that SAS uses to read data values into a variable. For example, the following value contains a dollar sign and commas: $1,000,000 To remove the dollar sign ($) and commas (,) before storing the numeric value 1000000 in a variable, read this value with the COMMA11. informat.Slide 55: Syntax of an Informat SAS informats have the following form: <$> informat < w >.< d > Here is an explanation of the syntax: $ indicates a character informat; its absence indicates a numeric informat. informat names the informat. w specifies the informat width d specifies an optional decimal scaling factor in the numeric informats.Slide 56: data tmp1; input ename $ edate ; informat edate ddmmyy8.; format edate date9.; cards; hari 10/10/07 ; run;Slide 57: Functions: De.nition of Functions A SAS function performs a computation or system manipulation on arguments and returns a value. Syntax of Functions: The syntax of a function is as follows: function-name ( argument-1 <..., argument-n >) x=max (cash,credit); x=sqrt(1500);Slide 58: Statements Definition of Statements A SAS statement is a series of items that may include keywords, SAS names, special characters, and operators. All SAS statements end with a semicolon. INPUT, List PUT , DATALINES DO Iterative DO Until DO While SELECT, DROP MERGE ,SET FILE , LENGTH Sum, END OUTPUT, KEEP, DATA, RETAINSlide 59: SAS System Options System options are instructions that affect your SAS session. Syntax of SAS System Options The syntax for specifying system options in an OPTIONS statement is OPTIONS option(s) ; Here is an explanation of the syntax: option specifies one or more SAS system options that you want to change. options nodate linesize=72;Slide 60: STANDARD DATA: The data values are in the standard format then the data is called standard data Eg: 467 NON STANDARD DATA : If data values are not in the standard format then data is called as non-standard data. Eg: 18-10-05 45,000 $21,000Slide 61: Informats are used to read non-standard data : data dates; input name $ Bdate: ddmmyy8. ; format Bdate: ddmmyy8.; cards; hari 21-10-84 ravi 22-11-86 ; run ;Slide 62: Date Informats: Date Informat Format 12-07-78 DDMMYY8. DDMMYY8. 21-09-05 DDMMYY10. DDMMYY10. 22Jan89 Date7. Date7. 22jan1989 Date9. Date9.Slide 63: Numeric Informats: Numeric Informat Format 25,000 COMMA6. COMMA6. $3,000 DOLLAR6. DOLLAR6. 25,000 COMMA6. WORDS6.Slide 64: DEFINING VARIABLES IN SAS: INPUT statement provides instructions for reading data, it defines the variables for the data set that come from the raw data. SAS variables can have these attributes: _ name _ type _ length _ informat _ format _ labelSlide 65: DIFFERENT WAYS TO READ DATA: 1.RAW DATA IN THE JOB STREAM: You can place data directly in the job stream with the programming statements that make up the DATA step. The DATALINES statement tells SAS that raw data follows. The single semicolon that follows the last line of data marks the end of the data. The DATALINES statement and data lines must occur last in the DATA step statements:Slide 66: data weight_club; input IdNumber 1 - 4 Name $ 6 - 20 Team $ StartWeight EndWeight ; datalines; 1023 David Shaw red 189 165 1049 Amelia Serrano yellow 145 124 1219 Alan Nance red 210 192 1246 Ravi Sinha yellow 194 177 1078 Ashley McKnight red 127 118 ;Slide 67: 3.DATA IN A SAS DATA SET You can also use data that is already stored in a SAS data set as input to a new data set. To read data from an existing SAS data set, you must specify the existing data set’s name in one of these statements: _ SET statement _ MERGE statement Data Temp; Set weight_club; Run;Slide 68: 2.DATA IN AN EXTERNAL FILE: If your raw data is already stored in a file, then you do not have to bring that file into the data stream. Use an INFILE statement to specify the file containing the raw data. The statements in the code that follows demonstrate the same example, this time showing that the raw data is stored in an external file: data <dataset name>; infile ’your-input-file path\filename.extension’; input <var 1> <var 2> …….; run;Slide 69: 4.DATA IN A DBMS FILE: If you have data that is stored in another vendor’s database management system (DBMS) files, then you can use SAS/ACCESS software to bring this data into a SAS data set. SAS/ACCESS software enables you to assign a libref to a library containing the DBMS file. In this example, a libref is declared, and points to a library containing Oracle data. SAS reads data from an Oracle file into a SAS data set: libname dblib oracle user=scott password=tiger ; data employees; set dblib.employees; run;Slide 70: DATA SET OPTIONS: Data set options specify actions that apply only to the SAS data set with which they appear. They enable you to perform operations such as these: KEEP: This example uses the KEEP= data set option in the SET statement to read only the variables that represent the in Set Statement: Data samp; Set weight_club (Keep= IdNumber Team); Run;Slide 71: DROP: Use the DROP= option to create a subset of a larger data set when you want to specify which variables are being excluded rather than which ones are being included. The following DATA step reads all of the variables from the data set weight_club except for those that are specified with the DROP= option, and then creates a data set named A1. Data A1; Set weight_club (Drop= IdNumber Name); Run;Slide 72: OBS= : Specifies when to stop processing observations data s1 ; set weight_club(obs= 3 ); run ; Firstobs=: Specifies which observation SAS processes first data s1 ; set weight_club(obs=4 firstobs=2); run;Slide 73: RENAME=: Changes the name of a variable data two (rename=(name=Pname)); set weight_club; run; PW= : Assigns a read, write, or alter password to a SAS and enables access to a password-protected SAS. data two1 (Pw=ram) ; set weight_club; run;Slide 74: WHERE=: Selects observations that meets the specified condition data weight_club; ; Data tmp; set weight_club (where=(Name ="David Shaw")); run; IN=: Creates a variable that indicates whether the data set contributed data to the current observation.Slide 75: DATA STEP STATEMENTS: Data statement: Begins a DATA step and provides names for any output SAS data sets. Creating an Output Data Set data example1 ; set weight_club; run;Slide 76: When Not Creating a Data Set data _NULL_; set weight_club; put Name ; run;Slide 77: CARDS Statement: Indicates that data lines follow DATALINES Statement (New version): Indicates that data lines follow Using the DATALINES Statement In this example, SAS reads a data line and assigns values to two character variables, NAME and DEPT, for each observation in the DATA step:Slide 78: DELETE Statement: Stops processing the current observation if Team=“red” then delete; FORMAT Statement: Associates formats with variables INFORMAT Statement: Associates informats with variablesSlide 79: data two1; input ename $ eid hiredate ; informat hiredate mmddyy8.; datalines; hari 101 12/01/05 ravi 102 11/03/06 ; run;Slide 80: DATALINES4 Statement: or Cards4: Indicates that data lines that contain semicolons follow data biblio; input number citation $50.; datalines4; 6 1988 2 LIN ET AL., 1995; BRADY, 1993 3 BERG, 1990; ROA, 1994; WILLIAMS, 1992 ;;;;Slide 81: DM Statement: Submits SAS Program Editor, Log, Procedure Output or text editor commands as SAS Statements dm log ‘clear’; KEEP Statement: Includes variables in output SAS data sets data average; set weight_club; keep name team; run ;Slide 82: LABEL Statement: Assigns descriptive labels to variables data rtest; set weight_club; label name=teamname; run ;Slide 83: LENGTH Statement: Specifies the number of bytes for storing variables data testlength; input firstname$ lastname$ n1 n2; length name $25 ; datalines; Alexander Robinson 35 11 ;Slide 84: INPUT Statement: Reads input values from specified columns and assigns them to the corresponding SAS variables. This DATA step demonstrates how to read input data records with column input: data scores; input name $ 1-18 score1 25-27 score2 30-32;Slide 85: INPUT METHODS: 1)List INPUT METHOD 2)Column INPUT METHOD 3)NAMED INPUT METHOD 4)FORMATTED INPUT METHOD 5)ABSOLUTE INPUT METHODSlide 86: 1)List INPUT METHOD: In this method the data values should be seperated by at least single space. EG: -Do- 2)Column INPUT METHOD: In this method character data values contain more than 8 characters and it can contain blank spaces also.Slide 87: data temp; input id 1 - 3 name $ 7 - 18 age 21 - 22 ; cards; 101 shiva krish 38 102 ravi krish 38 103 rama krish 38 ; run ; 3)NAMED INPUT METHOD In this method data values are followed by variable names.Slide 88: data samp; input id= name= $ age=; cards; id=290 name=ravi age=20 id=291 name=rani age=19 ; run ; 4)FORMATTED INPUT METHOD In this method variables length followed by period to specify the length of the variable for all data values.Slide 89: data one; input id 3. name $ 11. age 3. ; datalines; 101 praveenraj 25 102 kiranraj 23 ; run ; 5)ABSOLUTE INPUT METHOD In this input method we are using column hold pointer to give exact location of data values.Slide 90: data two; input @ 1 id 3. + 5 @ 10 name $ 4. + 5 @ 19 age; cards; 102 hari 29 ; run ;Slide 91: Holding a Record Across Iterations of the DATA Step The INPUT statement uses the double trailing @ to control the input pointer across iterations of the DATA step. data test; input name $ age @@; datalines; John 13 Monica 12 Sue 15 Stephen 10 Marc 22 Lily 17 ;Slide 92: The INPUT statement in this DATA step uses the & format modifier with list input to read character values that contain embedded blanks. DATA AMPERS; INPUT NAME & $25. AGE GENDER : $1.; DATALINES; RASPUTIN 45 M BETSY ROSS 62 F ROBERT LOUIS STEVENSON 75 M ; PROC PRINT DATA=AMPERS; TITLE 'Example 4'; RUN;Slide 93: BY Statement: Controls the operation of a SET, MERGE, MODIFY, or UPDATE statement in the DATA step and sets up special grouping variables. In By group processing it creates two variables First. variable and last. variable Processing BY-Groups: FIRST. variable has a value of 1 for any preceding variable in the BY statement. In all other cases, FIRST. variable has a value of 0.Slide 94: LAST. variable has a value of 1 for any preceding variable in the BY statement. In all other cases, LAST. variable has a value of 0.Slide 95: Grouping Observations by City, State, Zip Code, and StreetSlide 96: data cnt; set demo3; by eid; if first.eid then ct=0; ct+1; if last.eid; run;Slide 97: FILE Statement: Specifies the current output .le for PUT statements PUT Statement: Writes variable values in the specified columns in the output lineSlide 98: Data samp; Input Pname $ PID Pwgt ; File 'D:\hari.txt'; put pname $ PID; cards; hari 444 789 ravi 555 878 ; run ;Slide 99: OUTPUT Statement: Writes the current observation to a SAS data set data response(drop=time1-time3); set sulfa; time=time1; output; time=time2; output; time=time3; output; run;Slide 100: IF Statement: Continues processing only those observations that meet the condition if sex=’F’; IF-THEN/ELSE Statement: Executes a SAS statement for observations that meet speci.c conditions if status=’OK’ and type=3 then count+1;Slide 101: SET Statement: Reads an observation from one or more SAS data sets data fitness; set health exercise well; run; data Raleigh. members; set nc.members; if city=’Raleigh’; run;Slide 102: RUN Statement: Executes the previously entered SAS statements LIBNAME Statement: Associates or disassociates a SAS data library with a libref (a shortcut name); Libname hari “D:\file”; Libname hari clear;Slide 103: RETAIN statement: The Retain statement prevents SAS from re-initializing the values of new variables at the top of the data step. Previous values of retained variables are available for processing across iteration of the data step. data samp; input patname $ patid; datalines; ravi 11 kiran 12 ramu 13 ramesh 14 rakesh 15 ganesh 16 venu 17 srinu 18 ;Slide 104: data temp; set samp; retain c1 c2; if patname='ramu' then c1=patid; else if patname="ganesh" then c2=patid; run;Slide 105: INFILE Statement: Identifies an external file to read with an INPUT statements Some Infile options: -DELIMITER= Alias: DLM= -The DSD option sets the comma as the default delimiter. -FIRSTOBS= record-number specifies a record number that SAS uses to begin reading input data records in the input file. -OBS= read a range of recordsSlide 106: data num; infile datalines dsd; input x y z; datalines; 1,2,3 4,5,6 7,8,9 ; data nums; infile datalines dsd delimiter='*'; input X Y Z; datalines; 1*2*3 4*5*6 7*8*9 ;Slide 107: data weather; infile datalines missover; input temp1-temp5; datalines; 97.9 98.1 98.3 98.6 99.2 99.1 98.5 97.5 96.2 97.3 98.3 97.6 96.5 ;Slide 108: Sum Statement: Adds the result of an expression to an accumulator variable data cnt; set demo3; by eid; if first.eid then ct=0; ct+1; if last.eid; run;Slide 109: END Statement: Ends a DO group do; statements end; DO Statement, Iterative: Executes statements between DO and END repetitively based on the value of an index variable. data tc; do i=1 to 10; i+1; end; run;Slide 110: DO UNTIL Statement: Executes statements in a DO loop repetitively until a condition is true. Data temp; n=0; do until(n>=8); put n=; n+1; end; run;Slide 111: DO WHILE Statement: Executes statements repetitively while a condition is true n=0; do while(n<5); put n=; n+1; end;Slide 112: MERGE Statement: Joins observations from two or more SAS data sets into single observations Example 1: One-to-One Merging This example shows how to combine observations from two data sets into a single observation in a new data set: data benefits.qtr1; merge benefits.jan benefits.feb; run;Slide 113: Example 2: Match-Merging This example shows how to combine observations from two data sets into a single observation in a new data set according to the values of a variable that is specified in the BY statement: data inventry; merge stock orders; by partnum; run;Slide 114: FUNCTIONS: Defenition of Functions: A SAS function performs a computation or system manipulation on arguments and returns a value. Syntax of Functions: The syntax of a function is function-name ( argument-1 <, ... argument-n >)Slide 115: Scan Function: Scan function extract a word from a string. Example: In the below example scan function extracts ‘ram’ word from sd and stores it into a new variable cs. data n; sd='hari kris ram ganesh'; cs=scan(sd, 4 ); run ;Slide 116: INDEX Funtion: INDEX Function searches position of a string. Example: In the below example INDEX function searches position of ‘r’ and prints it in to a new variable. Data samp; gd='ganesh hari'; sc=index(gd,'r'); Run;Slide 117: LENGTH Function : Returns the length of a character string. Example: In the below example it returns the length of ‘ganesh hari’ into a new variable. data temp3; fg='ganesh hari'; ds=length(fg); run ;Slide 118: SUB STRING Function: Extract a substring from a character string. Example: In the below example it extract the 1 to 5 substring stores into a new variable dp. Data samp1; sg='ganesh'; dp=substr(sg, 1 , 5 ); Run;Slide 119: UPCASE Function: Translates the letters to lower case to upper case. Example: In the below example ‘ganesh’ is translated to ‘GANESH’. DATA temp1; ps='ganesh'; tp=upcase(ps); Run;Slide 120: LOWCASE Function: Translates the letters to upper case to low case. Example: In the below example ‘GANESH’ is translated to ‘ganesh’. Data temp2; rr='GANESH'; ss=lowcase(rr); Run;Slide 121: LEFT Function: Left aligns a SAS character expression Data demo1; a=’ DUE DATE’; b=left(a); put b; Run; MAX Function: Returns the largest value Data acnt; x=max(8,3); Run;Slide 122: MEAN Function: Returns the arithmetic mean (average) Data demo2; x1=mean(2,.,.,6); Run; 4 Data demo3; x2=mean(1,2,3,2); Run; 2Slide 123: MIN Function: Returns the smallest value x=min(7,4); 4 MOD Function Returns the remainder from the division of the .rst argument by the second argument, fuzzed to avoid most unexpected . oating-point results x1=mod(10,3); put x1 ; 1Slide 124: INPUT Function: Use INPUT to convert character values to numeric values If the INPUT function returns a value to a variable that has not yet been assigned a length, by default the variable length is determined by the width of the informat.The INPUT function enables you to read the value of source by using a specified informat.Slide 125: data testin; input sale $9.; fmtsale=input(sale,comma9.); datalines; 2,115,353 ;Slide 126: PUT Function: Use PUT to convert a numeric value to a character value. If the PUT function returns a value to a variable that has not yet been assigned a length, by default the variable length is determined by the width of the format. The format must be the same type (numeric or character) as the value of source. The result of the PUT function is always a character string.Slide 127: data temp; num=15; char=put(num,hex2.); ;Slide 128: SYSTEM OPTIONS: De.nition of System Options System options are instructions that affect your SAS session. DATE System Option: Prints the date and time that the SAS session was initialized FIRSTOBS= System Option: Speci.es which observation or record SAS processes .rst options firstobs=11; data a; set old; /* 100 observations */ run;Slide 129: OBS= System Option: Speci.es when to stop processing observations or records options firstobs=2 obs=12; proc print data=Ages; run; PAGESIZE= System Option: Specifies the number of lines that compose a page of SAS output PAGENO= System Option: Resets the page number You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.