A comprehensive, simple, and visual guide to data analysis using SAS programming, this course is simplified into 4 main areas: data preparation, data structuring, data visualization, and optimizing code using powerful SAS macros.
About This Video
A comprehensive, simple, and visual guide to data analysis using SAS programming, this course is simplified into 4 main areas: data preparation, data structuring, data visualization, and optimizing code using powerful SAS macros.
About This Video
In Detail
This course is for absolute beginners as well as advanced users who wish to learn SAS programming. Delivered in a highly visual style, these immersive lectures will equip you with the cutting-edge tool used in many industries, primarily in pharma, finance, and insurance areas.
Simplified into just 4 main areas, this course is an accelerated path to learning SAS programming. Data preparation will teach you how to import data from multiple sources, create new variables, write SAS functions, and understand what goes on behind the scenes in SAS datasets. Data structuring will make you leap into transforming data to a new level by merging and joining multiple datasets together, or turning them upside-down (sorting) and sideways (transposing). Data visualization will propel you further into the world of analytics and obtain insightful inferences from what is inside your data.
The final section will take you into the world of macro programming that teaches you how to write your code professionally and elegantly.
At the end of the course, you will try out most concepts discussed in this course through a coding exercise that will take you through these sections in preparation for your own SAS certification.
Audience
This course is designed for individuals looking to quickly acquire data manipulation and data analytics skills in order to get placed in job roles that involve a lot of data processing, or as part of data science university coursework, or to pass the Base SAS or Advanced SAS certification. No prior experience is required. This course uses SAS OnDemand for Academics Edition as the software tool to work with data.
Chapter 1 : Why Learn SAS
Course Overview
Chapter 2 : Getting Started with SAS Programming
Why is SAS so Easy to Learn
SAS Studio through SAS OnDemand - Registration
Logging In to a SAS Session after Installation
SAS User Interface
Chapter 3 : Preparing Data
Section Overview
SAS Dataset, Variables, and Observations
SAS Libraries
Library Naming Conventions
Dataset Naming Conventions
SAS Program Syntax
SAS Data Step and Proc Step
Referencing Data in SAS
Bringing Data into SAS
Bringing Data into SAS Using the Import Wizard
Bringing Data into SAS Using the LIBNAME Statement
Bringing Data into SAS Using the FILENAME Statement
Bringing Data into SAS Using the DELIMITER Option
Bringing Data into SAS Using the DSD Option
Bringing Data into SAS Using Column Input
Bringing Data into SAS Using Column Pointer @ Symbol
Bringing Data into SAS Using the Line Pointer # Symbol
Bringing Data into SAS Using Line Pointer Slash Symbol
Bringing Data into SAS Using the Trailing @ Symbol
Bringing Data into SAS Using the Trailing Double @ Symbol
Bringing Data into SAS Using Proc Import for XLS (MS Excel) Files
Bringing Data into SAS Using Proc Import for TXT Files
Creating New Variables
Creating New Variables - Code
Keeping, Dropping, and Renaming Variables in a Dataset
If-else Conditional Statements - Deriving BMI Variable
If-else Conditional Statements - Deriving STATUS Variable
Filtering Data
SAS Dates
SAS Functions - Upcase
SAS Functions - Lowcase, Propcase, Len, Cat
SAS Functions - Substr
SAS Functions - Trim, Left, Strip, Compress, Compbl
SAS Formats - Introduction
Format Statement
Format Naming Conventions
Format Using the PUT Function
SAS Informats
SAS Informats - Code
Custom Formats Using Proc Format
Custom Formats Using Proc Format - Code
Program Data Vector (PDV)
Implicit Output- Descriptor Portion
Implicit Output - var and Data Portion
Explicit Output
Explicit Output - Code
Do Loops
Guided Exercise – ‘Project Cars’ - Introduction
Section Conclusion
Chapter 4 : Structuring Data
Section Overview
Stacking Data Using a Data Step
Stacking Data Using Proc Append
Stacking Data Using Proc Append - Code
Interleaving of Data
Sorting Data Using Proc SortT
Sorting Data Using Proc Sort - Multi-Level Sorting
Removing Duplicates - NODUP Option
Removing Duplicates - NODUPKEY Option
Simple Merging of Data
Merging Data Using Joins - Introduction
Merging Data Using Inner Join
Merging Data Using Inner Join - Code
Merging Data Using Full Join.
Merging Data Using Left Join
Merging Data Using Right Join
Merging Data Using ‘Far’ Joins
PROC SQL - Copying Data
Proc SQL - Copying Data - Code
Proc SQL - Filtering Data
Proc SQL - Sorting Data
Proc SQL - Removing Duplicates
Transposing Data - ID Statement
Transposing Data - ID Statement - Code
Transposing Data - BY Statement
Transposing Data - BY Statement - Code
Retain Statement - Introduction
Retain Statement - How to Use
Retain Statement - Example
Section Conclusion
Chapter 5 : Visualizing Data
Section Overview
Charts - Introduction - Vertical Bar Chart
Charts - Horizontal Bar and Pie Charts
Vertical Bar Chart - DISCRETE Option
Horizontal Bar Chart - DISCRETE Option
Vertical Bar Chart - Groups and Subgroups
Horizontal Bar Chart - Groups and Subgroups
Plots
Report Output Using Proc Print
Report Output Using Proc Report - DISPLAY Option
Report Output Using Proc Report - ORDER and GROUP Option
Summary Statistics - Proc Freq
Summary Statistics - Proc Means
Summary Statistics - Proc Univariate
Output Delivery System (ODS) - Report Formats
ODS with Proc Freq
ODS with Proc Means
ODS with Proc Univariate
Section Conclusion
Chapter 6 : Optimizing Code
Section Overview
Macro Variables - Introduction
Macro Variables - Introduction - Code
Application of Macro Variables
Application of Macro Variables - Code
Nested Macro Variables and Ampersand Resolutions
More on Ampersand Resolutions Using a Cool Example
SAS Macros - Introduction
SAS Macros - Examples
Macro Functions
Macro Functions - Code
Optimizing Code - Section Conclusion
Chapter 7 : Practice Exercise | Case Study
Guided Exercise – ‘Project Heavy-weight’ - Introduction to the Project and Data