SAS for Microsoft 365 enables seamless integration between SAS and Microsoft applications—making it easy to upload data from Excel directly into SAS and CAS libraries. This post will demonstrate how to update a data source in Excel and instantly see the changes reflected in your SAS Visual Analytics reports -- all without ever leaving Excel!     Building on a Previous Post   A previous post Uploading Tables to SAS and CAS Libraries using SAS for Microsoft 365  showed how to upload data on common animals found in Glacier National Park to a SAS library. Since then, the data was imported into a CAS library and used to build a SAS Visual Analytics report called Animals of Glacier NP.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   This report gives a simple overview of the animals of the park, including the ratio of mammals to birds, an analysis of the relationship between average weight (lbs) and lifespan (years) along with a list table of all animals in the data.   The Great Gray and Boreal owls also inhabit the park, so let's update the report to include their data as well.     Open Your Data in Excel   Start by opening the Glacier Excel file on your local machine. From the top ribbon in Excel, select SAS, then log in using SAS credentials. Next, navigate to the Reports tab and open the Animals of Glacier NP report.       Update the Data   To include the Great Gray and Boreal owls, append their information to the Excel worksheet. Then, click Upload Data from the SAS ribbon, select the CASUSER library where the GLACIER table is stored, and replace the existing table with the updated version. From the SAS Pane, choose More Options > Reopen Report—and just like that, the report contains the updated data!       Conclusion   With just a few clicks, we've updated the data and refreshed the report—all without leaving Excel. This integration truly simplifies the analytics workflow, making it easier to keep your reports current and data-driven.   To learn more about what’s possible with SAS for Microsoft 365, check out:   SAS for Microsoft 365 | SAS Support   Uploading Tables to SAS and CAS Libraries using SAS for Microsoft 365   Course: SAS for Microsoft 365     Find more articles from SAS Global Enablement and Learning here. ... View more

In today's data-driven world, organizations need tools that combine powerful analytics with accessibility. SAS enables users to build sophisticated statistical models, while Microsoft Excel remains a staple for data organization and reporting. By using SAS for Microsoft 365, users can seamlessly integrate SAS’s modeling capabilities with Excel’s familiar interface, leveraging the strengths of both platforms. In this post, we'll leverage SAS for Microsoft 365 to analyze factors contributing to a Congenital Heart Disease (CHD) diagnosis using a logistic regression model in SAS, and then highlight our findings in Excel.   Framingham Heart Study   For this analysis, we will be using the SASHELP.HEART table which provides results from the Framingham Heart Study which originates from a long-term cardiovascular study conducted in Framingham, Massachusetts, beginning in 1948. This dataset is widely used in epidemiological research to analyze risk factors for heart disease. It contains demographic, lifestyle, and clinical variables such as age, sex, weight, cholesterol levels, blood pressure, and smoking status, among others. The dataset has been instrumental in identifying key predictors of cardiovascular disease and remains a valuable resource for statistical modeling and machine learning applications in healthcare.   Inserting SAS Data into Excel   We'll start by creating a new workbook in Microsoft Excel, opening the SAS Viya pane, and navigating to the Data tab. From there, users can select a cataloged table or choose one from the CAS or SAS Compute Servers. Since SASHELP.HEART is located on the SAS Compute Server, we'll select All Tables from the dropdown menu, then navigate to SAS Studio Compute Context > SASHELP > HEART to open the table.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   After double-clicking the SASHELP.HEART table, the Results tab opens, allowing us to modify the table before inserting it into the workbook. To add all rows to the worksheet, we select All rows from the Insert rows dropdown menu. In the Table Options section, we check Display column labels and leave the remaining options unchecked.     In the Columns tab, we can choose which columns to insert into the workbook. We select the following:   Status: Alive or Dead   AgeCHDdiag: Age at CHD Diagnosis   Sex: Male or Female   AgeAtStart: Age at the start of the study   Chol_Status: Cholesterol Status: Desirable, Borderline, High   BP_Status: Blood Pressure Status: Optimal, Normal, High   Weight_Status: Weight Status: Underweight, Normal, Overweight   Smoking_Status: Smoking Status: Non-smoker, Light, Moderate, Heavy, Very Heavy   We will reorder the columns by selecting the Reorder icon  , selecting the AgeCHDdiag column and using the arrows on the side to move it below AgeAtStart. If the arrows do not appear, try dragging the left-hand side of the SAS Viya pane to make it larger.     The Filter tab contains the Graphical and Expression builders to filter data by rows. The Graphical Builder provides a user-friendly, drag-and-drop interface for creating queries, making it easier for users to build and manipulate data without writing code. In contrast, the Expression Builder allows users to create custom expressions, calculations, and conditional logic using functions and operators, offering more flexibility for advanced data transformations.   We are not going to filter our data, so let's go to the Sort tab and sort the table by AgeAtStart in ascending order by selecting Add sort, choosing AgeAtStart from the dropdown menu and ensuring the Sort icon is set to ascending  .     Select the Insert in document icon  to insert the table into the Excel worksheet and label the worksheet tab Data. Notice in the data that some study participants have a value for Age CHD Diagnosed and others do not. We will run a logistic regression analysis to see what factors lead to participants being diagnosed with CHD.     Logistic Regression Analysis   Let's create another Excel worksheet called Analysis of CHD Diagnosis.     Navigating to the Programs tab of the SAS Viya pane, we'll use a SAS program to run a logistic regression analysis of factors contributing to CHD diagnosis.   In this SAS program, we are creating a new variable called CHDYes that is equal to 1 if the participant has a value for Age CHD Diagnosed and 0 if missing. Then, we use PROC LOGISTIC to run the a regression model with Sex, Age at Start, Cholesterol Status, Blood Pressure Status, Weight Status, and Smoking Status as explanatory variables for CHD Diagnosis.   /* Create a new dataset with CHDYes variable */ data heart_data; set sashelp.heart; if missing(AgeCHDDiag) then CHDYes = 0; else CHDYes = 1; run; /* Perform logistic regression with specific output */ ods graphics on; ods select ParameterEstimates OddsRatios ORPlot; proc logistic data=heart_data descending plots=oddsratio; class Sex Chol_Status(ref = "Desirable") BP_Status (ref = "Optimal") Weight_Status (ref = "Normal") Smoking_Status (ref="Non-smoker") / param=ref; model CHDYes = Sex AgeAtStart Chol_Status BP_Status Weight_Status Smoking_Status; run; ods graphics off;   Making sure the top left cell of the Excel worksheet is selected, click Insert in document to add the results of the regression analysis to the worksheet.     The regression analysis gave us a table of Maximum Likelihood Estimates along with a table and graph of Odds Ratio Estimates. To make it easier for viewers to hone in on statistically significant factors, we can use Excel to highlight the statistically significant factors in both tables.     From the analysis we see there are several statistically significant factors affecting the likelihood of a CHD diagnosis. For example, those who are classified as Overweight or Very Heavy smokers are more at risk of a CHD Diagnosis. We can use conditional formatting in Excel to highlight the cells with these values.     Males and those with a blood pressure status other than Optimal are more likely to be diagnosed with CHD. We can use Excel to create a new sheet called Blood Pressure Status by Sex and include a pivot table and pivot chart to understand the distribution of these two variables.     Conclusion From this analysis, we were able to use the statistical modeling capabilities of SAS with the familiar interface of Microsoft Excel, all while never leaving the Excel app. To learn more about SAS for Microsoft 365 visit SAS for Microsoft 365 | SAS Support or sign up for the new SAS for Microsoft 365 course to become an expert user: Course: SAS for Microsoft 365.     Find more articles from SAS Global Enablement and Learning here. ... View more

SAS for Microsoft 365 enables seamless integration of SAS analytics within Microsoft applications, enhancing productivity and presentation quality. In this post, we'll share practical tips for working with SAS Viya report objects in PowerPoint, including resizing and removing objects and modifying table values. While these demonstrations use the PowerPoint desktop app, they can also be applied in the web app.   For an introduction to using SAS for Microsoft 365 with PowerPoint, check out Using PowerPoint with SAS for Microsoft 365 as a Sales Storyteller - SAS Users   For more general information about SAS for Microsoft 365, visit SAS for Microsoft 365 | SAS.   Setting Up the Presentation   To begin, create a blank PowerPoint presentation and navigate to SAS Viya > Home to open the SAS Viya pane. For this demonstration, we’ll use the Warranty Analysis report, which analyzes warranty costs and trends across years, labor groups, and claims. You can access this report by selecting the Reports tab > SAS Content > Products > SAS Visual Analytics > Samples.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   Resizing a Plot to Fit the Space   When inserting the Cost by Primary Labor Group bar chart, you might notice that the x-axis tick labels are staggered. If you expand the chart to make it larger, it may initially appear distorted. To resolve this:   Expand the graph in the PowerPoint slide. Hover over the chart in the SAS Viya pane and click Object menu > Update in Document.   Alternatively, you can select the chart in the slide and click the Update in document icon  in the SAS Viya pane. This ensures the plot is redrawn to fit the expanded space without distortion.     Removing a Report Object from a Presentation   If a report object is no longer needed, your first instinct might be to click and delete it. However, doing so may cause issues if you later want to reinsert the same object—the Insert in document option will no longer be available.   To completely remove the object:   Hover over the object in the SAS Viya pane. Click Remove from document. You can now reinsert the object by selecting Insert in document.   Keep in mind that any customizations to the object's size or other features will reset to their default settings. You can adjust these defaults via the Home tab > More Options > Preferences.     Modifying Table Values   When you insert a details table, it is added as a graphic, meaning that you can’t modify the values directly. To make edits:   Select the table in PowerPoint. Go to the Graphics Format tab and click Convert to Shape.   This allows you to edit the table values, such as renaming the Primary Labor Group column to Main Labor Group. However, note that converting to a shape breaks the table’s link to SAS, so it can no longer be updated via the SAS Viya pane.     Conclusion   SAS for Microsoft 365 provides a powerful way to integrate SAS analytics directly into Microsoft PowerPoint, enabling users to create dynamic and visually compelling presentations. By following the tips outlined in this post—such as resizing objects, properly removing and reinserting objects, and modifying table values—you can maximize the flexibility and functionality of your presentations.   Whether you're exploring warranty data or presenting insights from another domain, SAS for Microsoft 365 empowers you to craft presentations that effectively communicate your story. Dive in, experiment, and let SAS help you bring your data to life!     Find more articles from SAS Global Enablement and Learning here. ... View more

SAS for Microsoft 365 allows users to integrate SAS Visual Analytics reports with Microsoft applications. One example of this is the ability to insert reports directly into Outlook emails and appointments. When inserting a report or report objects into an Outlook email, users have three options: insert the report objects individually into the email, include a web link to the entire report, or attach the report or specific report objects as a PDF. This post will focus on the various options available when attaching the report as a PDF.     Attaching Reports and Report Objects in Outlook   When using SAS for Microsoft 365 with Outlook, users can either attach single report objects or the entire report as a PDF file.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.     When attaching the entire report as a PDF, a window appears with several customization options.     Let's explore the Include appendix information, Expand clipped and non-visible content, Include details tables, Include cover page, and Cover page text options.     Include Appendix Information   The Include appendix information option adds a tag to each report object that links to an appendix at the bottom of the PDF file. The appendix gives information on alternative text for the object and any filters used before generating the object.   For example, the Warranty Analysis report includes a tree map of labor and material costs by labor code. Clicking the appendix tag takes the user to the appendix at the bottom of the pdf which outlines the tree map's alternative text, ranks, and filters.         Expand Clipped and Non-Visible Content   The Expand clipped and non-visible content option enables users to see all of the content for tables, crosstabs, gauges, and containers. This includes content that is only partially available in the layout of the page. Each object is displayed on a separate page at the end of the report. For example, the forecast graph on the Labor Group Analysis and Forecast report page of the Warranty Analysis report has three tabs: Gross Material Amount, Gross Labor Amount, and Total Claim Amount. If the Expand clipped and visible content option is checked, all three forecast graphs will appear in the PDF, the first being whichever was selected before generating the PDF and the other two will be included on separate pages at the end of the report.         Clicking the minimize icon on expanded content will link to where the original object is located in the PDF.       Include Details Tables   The Include details tables option adds a section at the end of the PDF that includes the details tables for all of the objects in the report that have details tables associated with them. You can access the details table associated with an object by clicking the maximize icon.       Include Cover Page and Cover Page Text   If you select Include cover page, a cover page prints the name of the report, the date the PDF was created, the user's name, and the number of pages. Use the Cover page text field to add additional text to the cover page.         Conclusion   As you can see, there are several ways to customize a report PDF in Outlook using SAS for Microsoft 365. For details about each option, visit SAS Help Center: Attaching Report Objects and Entire Reports as PDF, and for more detailed information about SAS for Microsoft 365, visit the following:   SAS for Microsoft 365 | SAS Support   Using Outlook with SAS for Microsoft 365 as a Creative Collaborator - SAS Users   Uploading Tables to SAS and CAS Libraries using SAS for Microsoft 365   Getting the Job Done: Connecting SAS Viya Jobs with SAS for Microsoft 365   SAS Programs with Excel using SAS for Microsoft 365     Find more articles from SAS Global Enablement and Learning here. ... View more

SAS for Microsoft 365 enables users to seamlessly integrate the capabilities of SAS with Microsoft applications. This post will illustrate how to upload existing Excel tables to SAS and CAS libraries using SAS for Microsoft 365. While demos in this blog were performed using the desktop version of Excel, they can also be performed in the Excel web app.   I recently visited Glacier National Park and saw a variety of animals including bears, goats, and eagles. Curious to learn more about the animals I saw, I created a table of the most common animals found in Glacier National Park. This table includes information on the species, color, average weight, and average lifespan of each animal. This table is saved in an Excel workbook called Glacier on my desktop and my goal is to upload it to a SAS library called ANIMALS.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   I open the Glacier workbook in Excel, click SAS Viya > Home on the top ribbon, and sign in with my credentials in the SAS Viya pane. I click anywhere on table and click the Upload Data icon.       A box appears that allows me to choose which cells of the table to include (the default is the entire table) and has an option to identify the first row as column names.     Note: If you forget to click on the table before clicking Upload Data, no columns are selected. To fix that, simply click anywhere on the table and select the Update with current Excel selection icon.       The table also displays column properties including the name, label, type, length, and format of each column. You can click a column and the Edit column properties icon to change any of the column properties.       Going back to the Glacier data, I don't want to make any changes to the column properties so I click Upload data and a list of available SAS libraries appears. I select the ANIMALS library as the location for the table, call the table Glacier, and click Save as.     If I wanted to save the table to a caslib, I could click the Create a default CAS session and assign SAS librefs for existing caslibs icon. Available caslibs appear in the list of connected libraries.       Using the Upload data feature allows users to quickly and easily upload existing tables to libraries directly in Excel and does not require any programming to do so. To learn more about SAS for Microsoft 365 please visit SAS for Microsoft 365 | SAS Support.     Find more articles from SAS Global Enablement and Learning here. ... View more

SAS Viya jobs are a great tool to simplify commonly run SAS programs and provide users the ability to customize tables and reports. This blog will demonstrate how to use SAS Viya jobs with SAS for Microsoft 365. While the demonstrations in this blog were conducted using the Excel desktop app, they can also be performed in the web app.   What is a SAS Viya Job?   SAS Viya jobs can be used for a wide variety of purposes, such as web reporting, performing analytics, building web applications, and delivering content to clients. A SAS Viya job includes both a program and its definition, which contains details like the job name, author, and creation date and time. Users interact with the job by making selections using HTML forms or task prompts, and those selections are passed to the SAS program as macro variables. The SAS program runs, and the results are provided back to the user.   For more information on SAS Viya jobs, visit SAS Help Center: SAS Studio Developer’s Guide: Working with Jobs or check out the Working with SAS Viya Jobs course.   What is SAS for Microsoft 365?   SAS for Microsoft 365 enables users to seamlessly integrate the capabilities of SAS with Microsoft applications. Users can add reports directly to Excel workbooks, PowerPoint presentations, Outlook emails, and Word documents. They can also add reports and data created with SAS programs and SAS Viya jobs to Excel workbooks.   For more information on SAS for Microsoft 365, visit SAS for Microsoft 365 | SAS Support   Use Case: Dynamic Prompts Using CARS Data   Let’s take a look at a sample Viya job titled Dynamic Prompts using CARS data. This job utilizes the SASHELP.CARS table and allows users to filter vehicles by make and model, then creates a report on the selected vehicles.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   Note: If you would like to follow along while reading this blog, you can install the Dynamic Prompts Using CARS Data SAS Viya job by following these steps: Log into your SAS Viya environment. From the applications menu in the upper left corner, select Develop Code and Flows to open SAS Studio. Notice the URL ending /SASStudio/. Change it to /SASJobExecution/.  Next, click the Samples icon in the left navigation menu    to access the samples administration page, where you can view a table of available sample jobs. To install the Dynamic Prompts Using CARS Data SAS Viya job, select the job and click Copy To. In the folder selector window, select a destination folder where you have writable access and then click OK to copy the sample job. If an item already exists in that location, an option to skip, replace the item, or quit copying is presented.    To open SAS for Microsoft 365, click SAS Viya --> Home from the top ribbon of Excel.     To access the job, go to the Reports tab and navigate to the folder where the Dynamic Prompts using CARS data job is stored.     Right-click the job and open it in the Results tab.     The Results tab allows users to select values of prompts, view the log, and view the results of the job. In this example we’ll choose Saab for the vehicle make, Sedan as the vehicle type, and will not show the SAS log.     Once I’ve chosen values for each prompt, I click Run   and view the results of the job. We see a report with information on Saab sedans including the Model, Engine Size, Horsepower, and MSRP.     To add this output to my Excel workbook, I first select where in the worksheet I want to insert the report. In this case, I choose the top left corner of my worksheet.     In the SAS Viya pane, I click the Insert in document icon .       Now the report appears in my worksheet in the location I selected.   Let’s say I instead wanted the report to display information on BMW SUVs. I change my prompts and run the job.     The updated report appears in the Results tab.     To update the report in the Excel workbook, I click the Update in document icon  and the report is updated in the Excel worksheet. I also rename the Excel worksheet to BMW Report by double-clicking Sheet1 at the bottom of the worksheet and renaming it.     Now, say I wanted both the Saab and BMW reports, just on different sheets. I would first unlink the BMW report from SAS by selecting the report in the worksheet, clicking the Selected Object button on the top ribbon, and selecting Unlink from SAS. Doing this disconnects the report from the Viya job and it can no longer be updated using SAS data.     Now that the BMW report is disconnected from the Viya Job, I create a new Excel worksheet by clicking the plus at the bottom of the worksheet and rename Sheet2 to Saab Report.     I click the top left cell of the worksheet as the location of the report, then go to the SAS Viya pane to select Saab as the vehicle make and Sedan the vehicle type and run the job.     Finally, I insert the report into the worksheet by clicking the Insert in document icon .     Conclusion   SAS for Microsoft 365 is a great way to combine the powers of SAS Viya jobs and Excel. For more information on using SAS Viya jobs in Excel, SAS Help Center: Working with SAS Viya Jobs in Excel.     Find more articles from SAS Global Enablement and Learning here. ... View more

SAS for Microsoft 365 enables users to seamlessly integrate the capabilities of SAS with Microsoft applications. This post will focus on leveraging SAS programs to enhance Microsoft Excel workbooks using SAS for Microsoft 365. While the demonstrations in this post were conducted using the Excel desktop app, they can also be performed in the web app.   For more information on SAS for Microsoft 365, visit SAS for Microsoft 365 | SAS.   Embedding a SAS Program   Since we are in the midst of baseball season, let’s analyze the baseball table from the SASHELP library. This table includes information on players' statistics, teams, leagues, divisions, positions, and salaries.    Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   I want to create an Excel workbook analyzing the salaries of National League players. Upon opening Excel, I notice the SAS Viya tab in the ribbon at the top and click SAS Viya --> Home.     The SAS Viya pane appears on the right side of the workbook. Navigating to the Programs tab, I see a green checkmark next to Program1, indicating that I am connected to the SAS Computer server, which is necessary for writing or using an existing SAS program.       Renaming a Program   The Programs tab features the same tabs for code and the log that are present in SAS Studio. By default, my program is named Program1, and any additional programs would be named Program2, Program3, and so on. To rename my program, I click the More options icon  → Rename program and call this program National_Analysis.           Inserting Results into a Workbook   I want to write a program that filters the baseball data to include only players in the National League, displaying their name, team, league, and salary information. As I start typing, I notice the editor color-codes keywords and provides suggestions.   data National; set sashelp.baseball; where League = "National"; keep Name Team League Salary; run;     Once I finish my program, I click “Run”, and the Output Data tab appears with my new table work.National. To insert this table into my workbook, I click the Open icon , which opens the table in the Results tab. From here I can insert the table into my workbook by clicking the Insert table in document icon  .     Updating Results   I go back to the code and filter to only include players whose salary exceeds 500. I run the program, and notice my workbook is not immediately updated. To fix this, I go to the Results tab and click the Update in document icon  . This will apply any changes I made to the program to the results in the workbook.   data National; set sashelp.baseball; where League = "National" and Salary gt 500; keep Name Team League Salary; run;     In my program I can create multiple tables and reports, adding them wherever I would like in the Excel workbook. For example, here I create a PROC MEANS report on Salary and insert it into the workbook.   proc means data = National; var Salary; run;       Saving a SAS Program   Embedded SAS programs are created within an Excel workbook with SAS for Microsoft 365. They are accessible within the workbook, however if I wanted to use this program elsewhere, let's say in a new workbook, I would not have access to the program. I can instead save any programs I create as external programs by clicking the More options icon  --> Save as and navigating to the folder where I want to save the program. The program can now be accessed outside of the workbook where it was created.        Using a Previously Created SAS Program   If I want to use an external program created previously, I can simply open the program from the SAS Viya Pane by going to the Programs tab, clicking the More options icon  --> Open program.      If while working with this program my teammate or boss updates it, I must refresh the program by going to the Programs tab, click the More options icon  --> Refresh program. SAS for Microsoft 365 reopens the program and displays the latest version of the code.        Unlinking Results from SAS   Let’s say I want to save a copy of my results, unlinking my results from my SAS program. I can do so by selecting the results in my workbook --> the Selected Object icon in the SAS Viya ribbon --> Unlink from SAS. I notice the Update All and Selected Object options are now disabled.            Finding Results and Programs   I continue analyzing the baseball data and end up with several tables, reports, and graphics, making it hard to keep track of everything. If I want to find the objects associated with a program,  I can go to the Programs tab -->  select the program I am interested in, in this case American_Analysis.sas, where I analyzed the salaries of players on the American League --> the More options icon  --> Find in document, and the results associated with the program will appear in the workbook.   Code to create American_Analysis.sas: data American; set sashelp.baseball; where League = "American"; run; proc means data=American; var Salary; run; proc univariate data = American noprint; histogram Salary; run;       I can also go the opposite direction, selecting the results in the workbook --> Selected Object --> Find in SAS Pane. The program that created the results will pop up in the Programs tab.        Closing a SAS Program   To close a program in the SAS pane, I click the More options icon  --> Close, or Close all programs. I can either keep or remove the inserted content from the workbook. If I keep the results in the workbook, they are disconnected from SAS and cannot be updated. To get an updated version, I would need to open and run the SAS program and re-insert the results into the workbook.       Conclusion   SAS for Microsoft 365 is an efficient way to utilize SAS and Microsoft tools together, with the Programs tab allowing users to customize their workbook to their liking. For more information on SAS for Microsoft 365, visit SAS for Microsoft 365 | SAS Support. For more information about the Programs tab, visit SAS Help Center: Working with SAS Programs in Excel.     Find more articles from SAS Global Enablement and Learning here. ... View more

Coming to SAS after 6 years of almost exclusively programming in R, I was thrilled to discover ways to combine the strengths of both languages with tools like the R SWAT Package and PROC IML. Most recently I tried the R Runner custom step in SAS Studio Flows, which allows users to code in R, or even upload an entire R script to be used in a flow. The purpose of this post is to share my experience using R Runner and how anyone building a flow may benefit from it.   SAS Studio Flows   If you are asking yourself, “What is a ‘flow’?”, SAS Studio Flows offer a low-code option for analyzing data with SAS Viya. A flow is a sequence of operations on data. Data and operations are represented in SAS Studio by steps that you can access from the Steps section of the navigation pane. Each step in a flow is represented by a node on the flow canvas. While SAS provides several predefined steps to use in flows, users and developers also build custom steps to perform specific tasks. R Runner is a custom step that allows users to run R scripts and write R code to analyze data within a flow.   Here are some additional resources regarding SAS Studio Flows: Quick Start Video Documentation SAS Studio Flow Course   Set Up   I accessed R Runner through the SAS Studio Custom Steps GitHub repository which is available to all users.   My first step was to make sure my machine had the necessary requirements for R Runner. I asked my SAS Administrator for the following, which are outlined in more detail here:   A Viya 4 Environment 2023.08 or later. SAS Viya needs access to an active Python and R environment. The rpy2 Python package is installed and configured. A path to R is available through the R_HOME environment variable. Option to run R within SAS Studio compute sessions is enabled with the -RLANG system option Recommended: Administrators could make use of the SAS Configurator for Open Source (also commonly known as sas-pyconfig) to install and configure Python and R access from SAS Viya.   Once my environment was set up, I needed to upload the R Runner custom step into SAS Viya following the steps outlined here.   *Before continuing, view a tour of the R Runner interface here to familiarize yourself with the interface.   Using R Runner   Now that R Runner was ready to go, I did what any programmer would do and began my exploration by using the text box to print the ever-famous line, “Hello World!”    Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   Navigating to the “Submitted Code and Results” log, I found the output of my R Code.     Next, I submitted a regression model with the following steps to analyze the SASHELP.CARS table to understand the relationship between Horsepower and Highway MPG.   Right-click on the R Runner step and select Add input port.   From the Libraries pane, select the SASHELP.CARS table and drag it to the flow and connect it to the R Runner input port. This allows me to reference the input data source using the generic table name, r_input_table. (For more detail, click here).   Add the model code to the textbox. Notice instead of supplying CARS for the table name, I specified r_input_table. model <- lm(MPG_Highway ~ Horsepower, data=r_input_table) print(summary(model))     Run the flow and navigate to the “Submitted Code and Results” log. The program returns a summary of the regression model.   In addition to printing R output, R Runner has the ability to modify SAS tables with R code within a flow.   For example, let’s say I want to filter the SASHELP.CARS table by Make, only keeping Audis. The tidyverse set of packages in R includes convenient data transformation functions. tidyverse was installed with the SAS Open Source Configurator so all I needed to do was build my flow and include library(tidyverse) in my R code to load in the tidyverse packages. To create a table with only Audi vehicles included, I followed these steps:   Follow steps 1 and 2 of the previous example to connect SASHELP.CARS to R Runner. Right-click R Runner and add an output port, selecting outputtable.   Right-click the output port and add a table, providing the library WORK and table name AUDI.     Click R Runner again and add code to the textbox. library(tidyverse) AUDI <- r_input_table %>% filter(Make == “Audi”)   Provide a table name of AUDI to the “Provide name of R data frame…” textbox. This is used by R Runner to write to the defined output table.   Run the flow and navigate to the work library to open WORK.AUDI.   Submitting an R Script   Next, I put the same code in an R script and provided the location of the script to R Runner which gave the same results. This method is especially helpful to run longer programs and allows users to use the editing capabilities provided in an IDE such as R Studio to build the script, then execute it within a flow.       In some Viya environments, if using the folder button on the right, the path provided may not be complete. If you receive an error, find the location of your R script in the file system and copy/paste it to the text box instead with sasserver: in front of the path.           Data Visualization   You can even take advantage of R’s graphing capabilities within a flow. Below is an example creating a histogram using the ggplot2 package in R. This feature is limited to creating PDFs currently, but future developments will expand R Runner’s graphing capabilities.   I created a histogram of the Highway MPG data from SASHELP.CARS following these steps:   Connect the SASHELP.CARS dataset to R Runner following steps 1-2 from the previous examples. Add code to create and save the plot in the textbox. p <- ggplot(r_input_table, aes(x=MPG_Highway)) + geom_histogram(fill = “white”, color = “blue”) + ggtitle(“Highway MPG”) ggsave(“MPG_Hist.pdf”, p, path = “/home/student”)   Locate the PDF in your file directory.     Installing R Packages   When configuring R with SAS Viya using the SAS Configurator for Open Source, certain R packages are suggested as part of the installation manifest. If there are specific R packages you know you will need to use as part of your R script, please let your SAS administrator know so they can include those packages in the configuration. As of now, users cannot install R packages directly using R Runner.   Future Developments   R Runner developers are in the process of planning improvements and maintain an upstream repository for this purpose here.   Summary   R Runner serves as an excellent tool for integrating the capabilities of both R and SAS within flows. The most current version of R Runner can be accessed here.   References   R RWAT and PROC IML   SAS Studio Flows Quick Start Video   SAS Studio Flows Documentation   SAS Studio Flows Course   R Runner Communities Post   SAS Studio Custom Steps -- R Runner Git Repository   Custom Step Installation Instructions   R Runner Upstream GitHub Repository     Find more articles from SAS Global Enablement and Learning here. ... View more