SAS Programming

Explore the sas studio environment and use the proc print to generate a basic report from a dataset, illustrating how to print and view data with the results viewer.

Learn to use the SAS print procedure to display only selected variables from a data set, such as name, height, and weight.

Learn to suppress the observation number in SAS output and set an id variable to uniquely identify observations. The tutorial covers datasets, libraries, and id fields.

Learn to apply custom labels to variables in a SAS dataset and display them in the print output, including labeling age as 'age of employees'.

Learn how to use sum and n with the print procedure in SAS to summarize a numeric variable, display observations, and manage labels.

Use proc contents to generate a comprehensive data set report in SAS Studio, showing observations, variables, engine, creation order, type, length, format, and label.

Learn to use proc contents to generate a single contents report for all datasets in a library by applying data=libname._ALL_, saving time by inspecting multiple data sets at once.

Learn to use additional keywords with proc contents to tailor SAS dataset reports, suppressing itemized results and displaying directory information, with short and position chart options.

Learn to create data subsets in SAS by using first obs and obs to extract a range from an existing data set, saving the result as a new data set.

Apply keep and drop in the SAS data step to select or omit variables, create new datasets, and manage numeric and character variables with _numeric_ and _character_.

Learn to write basic where clauses in SAS to filter data by brand and numeric conditions, and use in, or, and operators with attention to case sensitivity.

Explore pattern matching in SAS using the where clause to filter data by contains, starts with, ends with, and logical or for words like chocolate or charcoal, creating new datasets.

Learn how to use if-then-else in SAS to apply conditions, create new variables and datasets, and implement multi-branch logic such as country-based status and height-based comments.

Demonstrate using the select when otherwise construct in SAS as a substitute for if-then-else, creating datasets and variables while applying conditional logic on height and country values.

Split a SAS data set by category into candy and nuts using if or select. Also demonstrate splitting into male and female subsets with a sex variable.

Learn to sort SAS datasets with proc sort by specifying variables for ascending or descending order, including multi-level sorts like category and subcategory.

In SAS programming, learn to sort an existing dataset and create a sorted replica in the work library, preserving the original data while ordering by height or weight.

Explore sorting data in SAS to identify unique values using nodup, by creating a sample dataset, applying the nodup technique, and comparing results to show how duplicates are removed.

Learn to find unique values in SAS using nodupkey and by variables, creating a dataset with nonduplicate observations and comparing results to verify deduplication.

Learn to create frequency distribution tables in SAS by counting values for categories like candy and nuts, displaying frequency, percent, and cumulative percent, and storing results in an output dataset.

Learn how to build cross tabulations in SAS to explore interactions between categorical variables, display frequency distributions, and interpret row and column percentages.

Learn how to create and refine cross-tabulations in SAS by using additional keywords, selecting fiscal year and quarter by category, and displaying frequency and percent with the list keyword, charts.

This lecture introduces the basics of the proc tabulate technique in SAS. It demonstrates creating tables from a numeric measure using category and subcategory variables with sum or mean.

Explore advanced tabulation in SAS by adding multiple numeric and categorical variables, constructing interactions between category, subcategory, fiscal year, and fiscal quarter, and customizing grid layouts for clearer insights.

Explore descriptive statistics in SAS by extracting information from numeric variables in a dataset, including mean, maximum, minimum, and observations, using three SAS procedures.

learn how to use proc summary technique in SAS to produce descriptive statistics, including n, mean, standard deviation, min, max, and missing values, with class by category and subcategory.

Explore descriptive statistics in SAS using proc means, viewing default statistics, selecting numeric variables, controlling decimals, and breaking down results by category and fiscal year with by-group analysis.

Learn how PROC UNIVARIATE in SAS generates descriptive statistics for numeric variables like age, height, and weight, including mean, standard deviation, minimum and maximum, with histograms to assess normal distribution.

Learn how to export SAS data files to csv using server-based folders, create a folder for export, specify the csv extension, and download the file for reuse.

Export SAS data to external text formats using delimited files with chosen delimiters such as comma, tab, or semicolon, via PROC EXPORT and specifying the output path.

Export SAS data to Excel formats, including Excel 97-2003 and Excel xlsx, using an output path and file name; verify the file format and access the downloaded Excel workbook.

Import csv files into a SAS data set in SAS studio by uploading to the server, then define the file location and create the data set in the work library.

Import text file formats to SAS data files using proc import, set the file location, and specify delimiters such as comma to import delimited data, including files with different delimiters.

Learn how to import Excel files into SAS data sets using proc import, handling both .xls and .xlsx formats in SAS programming.

Create a user defined character format in SAS using proc format to map M and F to male and female, then apply it in prints to visualize data clearly.

Create user defined numeric formats in SAS to convert numbers into days, register the format in a library, and apply it to visualize data more clearly.

Learn to compute date differences in SAS using the ddiff function and intck, handling year lengths 365/366 and month‑day fractions with actual/actual options for precise results.

Explore standard text functions in SAS, including converting text to uppercase, lowercase, and proper case, and extracting and replacing parts of text to transform textual data.

Explore SAS text functions and matching strings by extracting first, second, and third names with scan, then concatenating with separators and replacing words with tranwrd.

learn standard numeric functions in sas, including round and format to control decimals, and use sum and mean to aggregate crime rates by state into totals and averages.

Learn to transpose an existing data set in SAS by using a unique id variable to turn rows into columns. Save and label the transposed data set for easy analysis.

Join two SAS datasets by appending data step with the set statement, aligning common variables and creating a single dataset without sorting.

Merge and align data sets in SAS by appending while preserving common variables, using set statements, renaming fields to accumulate values into shared variables, and controlling dataset priority.

Merge two SAS datasets by a common key after sorting both datasets, ensuring unique observations, to produce a combined dataset that aligns on the key.

Explore left, right, inner, and outer merges in SAS by combining datasets with full, left, and right merges, prioritizing one dataset and including or excluding common observations.

Master one-to-many merges in SAS by combining a unique-observation dataset with a repeated-observation dataset, and learn the mapping process to create a single merged data set.

Explore many-to-many merging in SAS by combining two datasets with repeated observations using a by statement on iodine and drug, and observe how last observations repeat.

Learn how to use arrays in SAS to apply a single calculation across multiple columns. Convert Fahrenheit to Celsius for seven temperature observations using a do loop, automating the process.

Use arrays in SAS programming to calculate quarterly differences (Q2 minus Q1, Q3 minus Q2, Q4 minus Q3) and compute total incentives in a new dataset.

Learn how to import raw data in SAS with a data step and infile, specify column positions, create named variables, handle spaces, and manage missing values with the appropriate option.

Import raw delimited data with missing values in SAS using a comma delimiter and defined variables; handle missing fields and use shorthand to auto-create v1–vn, with gender as character.