SAS Programming Tutorial

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What is SAS tutorial?

SAS is popular software in business analytics. It provides huge innovative analytics to business intelligence and data management software and services. Unlike other tools it provides extensive programming approach to data transformation and analysis.

Audience

This tutorial is useful Data Analyst or Data Scientists. It is more useful for the readers who wish to seek transform raw data to produce insights for business using SAS.

Prerequisites

To learn this tutorial you should have basic knowledge of Computer Programming terminologies and awareness of any programming language, SAS programming concepts and SQL will be helpful.

SAS Programming Tutorial: List of Topics

• Input And Infile
  • Reading Raw Data Separated By Spaces
  • Reading Data Values Separated By Commas Or Other Delimiters
  • Applying An Inform At Statement To List Input
  • Reading Character Values That Contain Blanks
  • Reading Data Arranged In Columns
  • Reading Column Data That Require Informats
  • Reading Two Lines (records) Per Observation
  • Reading Parts Of Your Data More Than Once Features: @ Point Control
  • Using Informat Lists And Relative Pointer Controls
  • Reading A Mixture Of Record Types In One Data Step
  • Holding The Data Line Through Multiple Iterations Of The Data Step
  • Suppressing Error Messages
  • Reading Data From External Files
  • Reading In Parts Of Raw Data Files
  • Reading Data From Multiple External Files
  • Reading Long Records From An External File
• Data Recoding
  • Using If-then/else Statements To Recode A Variable
  • Using A Select Statement To Recode A Variable
  • Using Formats To Recode A Variable
  • Using A Put Function To Create A New Variable
• Set, Merge, And Update
  • Subsetting A Sas Data Set: Selecting Observations That Meet Certain Conditions
  • Combining Sas Data Sets By Adding Observations
  • Combining Sas Data Sets By Adding Variables
  • Adding Variables From One Data Set To Another Based On An Identifying Variable
  • Controlling Which Observations Are Added To The Merged Data Set
  • Creating More Than One Data Set At A Time
  • Performing
  • Updating A Master File From A Transaction File
• Table Lookup Tools
  • Simple Table Lookup (method 1 - Merging)
  • Simple Table Lookup (method 2 - Formats)
  • Looking Up Two Variables (method 1 - Merging)
  • Looking Up Two Variables (method 2 - Formats)
  • A Two-way Lookup Table
• Sas* Functions
  • Mathematical Transformations Of Numeric Variables
  • Choosing Every Nth Observation From A Sas Data Set
  • Rounding And Truncating Numbers
  • Computing Means And Sums Of Variables Within An Observation. Counting The Number Of Non-missing Values In A List Of Variables
  • Character-to-numeric Conversion, Using The Input Function
  • Numeric-to-character Conversion, Using The Put Function
  • Computing A Moving Average
  • Taking Substrings
  • Taking Substrings, Unpacking" A String
  • Reading Combinations Of Numeric And Character Data
  • Validating Data Values
  • Translating One Set Of Character Values To Another
  • Removing Blanks Or Other Characters From A String
  • Joining (concatenating) Two Strings
• Sas* Dates
  • Reading A Date From Raw Data
  • Creating A Sas Date From Month, Day, And Year
  • Computing Age
  • Extracting Day Of Week And Day Of Month From A Sas Date
  • Extracting Month And Year From A Sas Date
  • Counting The Number Of Years, Months, And So On, From A Given Date
  • Computing Exact Age In Years
  • Computing The Date After A Number Of Intervals
• Sas® Arrays
  • Substituting One Value For Another In A Group Of Variables
  • Substituting One Value For Another In All Numeric Variables
  • Substituting One Value For Another In All Character Variables
  • Restructuring A Sas Data Set: Creating Multiple Observations From A Single Observation
  • Restructuring A Sas Data Set: Creating Multiple Observations From A Single Observation (multidimensional Example)
  • Restructuring A Sas Data Set: Creating A Single Observation From Multiple Observations
• Retain
  • Creating A Subject Number In The Data Step: A Common Mistake
  • Creating A Subject Number In The Data Step Using Retain
  • Explicit Versus Implicit Retaining Of Values
  • Scoring A Multiple-choice Test Using Retain
  • Using Caution When Coding With Retain
  • Checking For A New Subject Number Using A Lag Function
  • Checking For A New Subject Number Using A Lag Function And A Trailing @
• Proc Print
  • Creating A Simple
  • Dropping Observation Numbers
  • Increasing Readability
  • Adding Column Totals And Subtotals, Observation Counts, And Footnotes
  • Using The Width=full Option
  • Using The Width=minimum Option
• Proc Means And Proc Uimivariate
  • Computing Totals And Using Proc Means To Create A Summary Data Set
  • Computing More Than One Statistic
  • Creating Unweighted Summary Statistics (step 1)
  • Creating Unweighted Summary Statistics (step 2)
  • Producing A Formatted Summary Report
  • Computing Values As Percentages Of All Observations
  • Creating A Summary Data Set That Contains A Median
• Proc Format
  • Formatting Values In A Questionnaire
  • Encountering A Subtle Problem With Missing Values, Formats, And Proc Freq
  • Resolving The Subtle Problem
  • Checking For Invalid Values: A Data Step Approach (setting Invalid Values To Missing)
  • Checking For Invalid Values: A Data Step Approach (separating Invalid And Missing Values)
  • Using A User-created Informat To Filter Input Data (setting Invalid Values To Missing)
  • Using A User-created Informat To Filter Input Data (separating Invalid And Missing Values)
  • Checking Ranges For Numeric Variables
  • Using Different Missing Values To Keep Track Of High And Low Value
  • Creating And Using An Enhanced Numeric Informat
  • Using A Sas Data Set To Create A Character Format
  • Using A Sas Data Set To Create A Numeric Format
• Proc Chart
  • Creating A Vertical Bar Chart
  • Creating A Horizontal Bar Chart With Statistics
  • Creating A Horizontal Bar Chart Without Statistics
  • Creating A Bar Chart That Displays Percentages
  • Creating A Bar Chart For A Continuous Variable (system-chosen Midpoints)
  • Creating A Bar Chart For A Continuous Variable (user-chosen Midpoints By Range)
  • Creating A Bar Chart For A Continuous Variable (without Discrete Option)
  • Creating A Bar Chart For A Continuous Variable (with Discrete Option)
  • Plotting Sums And Means Of Numeric Variables
  • Representing Two Variables On One Axis
  • Displaying Groups Within A Bar -- Character Variable
  • Displaying Groups Within A Bar - Numeric Variable
  • Creating Three-dimensional Block Charts
• Proc Plot
  • Producing A Simple Scatter Plot
  • Placing Multiple Plots On One Set Of Axes
  • Placing Multiple Plots On One Set Of Axes With Different Plotting Symbols
  • Using The Value Of A Third Variable As The Plotting Symbol
  • Labeling Individual Points
• Efficiency
  • Avoiding Unnecessary Data Steps-1
  • Avoiding Unnecessary Data Steps — 2
  • Processing Selected Raw Data Records Using If Statements
  • Processing Selected Sas Data Set Observations Using Where Statements In Procedures
  • Dropping Unnecessary Variables When Building A Sas Data Set From Raw Data
  • Dropping Unnecessary Variables When Building A Sas Data Set By Setting An Existing One
  • Using A Length Statement
  • Using If-then/else Statements Instead Of Multiple If
    statements
  • Arranging The Order Of Your If Statements
  • Using Multiple Or Operators Instead Of The In Operator
  • Using Data _null_ When Creating Reports
  • Saving Data In Sas System Files
  • Using Proc Datasets To Modify Variables
  • Using Proc Datasets To Modify Sas Data Sets
  • Using Proc Append To Join Similar Data Sets
  • Using A Retain Statement To Initialize Constants
  • Avoiding Unnecessary Sorts: Performing A Two-level Sort Instead Of A One-level And A Two-level Sort
  • Avoiding Unnecessary Sorts: Using A Class Statement When Possible
  • Making Your Sorts More Efficient: Sort Only What You Have To Sort
  • Making Your Sorts More Efficient: Using The Noequals Option