R in ThoughtSpot

Starting in May 2022, ThoughtSpot rebranded pinboards as Liveboards. For backward compatibility, we currently support internal processes and external methods that use the older naming convention.

Analyze your data with R scripts that ship with ThoughtSpot, and build visualizations and Liveboards based on the analytical insights you obtained. You can also create custom R scripts, and share them with your team.

R is a popular open source programming language for statistical computing, machine learning, and AI. ThoughtSpot makes R analysis available as a fully integrated feature.

We support R Deprecated 8.4.0.sw [LA] only in Falcon deployments (data imported into ThoughtSpot), and R integration is disabled by default. It is not available when creating connections and linking to external databases in real time.

Using R in ThoughtSpot

Users with the Can invoke custom R analysis privilege can run R scripts directly on search results.

Analysts and data scientists who are proficient in R can create and share custom scripts.

Users can leverage custom scripts and ThoughtSpot provided scripts, run pre-built R scripts on top of their search results, and share R visualizations as answers and Liveboards.

This article explains how to use R in ThoughtSpot both from an end user and scripting perspective, but is not meant as an R primer.

Understand R script requirements in ThoughtSpot

ThoughtSpot provides R as a service within a ThoughtSpot cluster. Permissions are restricted. This means the R script does not have permission to issue system commands.

The ThoughtSpot cluster has pre-installed the basic R packages. If your script requires a specific package, you must contact your ThoughtSpot cluster administrator.

ThoughtSpot internally transforms and binds an R script prior to sending it to the cluster’s R service. The system expects each script to have a well-defined structure, following this format:

####R SCRIPT####
<Fill script body>
<Fill column bindings here>

The scripts contain the column bindings, and the answer results appear as parameters in the R script. For each .param n in R your script, you must provide a corresponding binding. The following example illustrates an R script in a form suitable for ThoughtSpot:

####R SCRIPT####
df <- data.frame(.param0,.param1, ...);
write.csv(..., file=#output_file#, ...);

Notice that .param0 refers to the first column in column binding and .param1 refers to the second. Should you need a third binding, you would use .param2 and so forth.

The output of the script is either PNG (images) or CSV (comma-separated values, such as a table). This example script uses #output_csv# for an output in a CSV (tabular) format. Use #output_png# for an output in PNG format.

Presently, error reporting for R scripts in SpotIQ is limited. You must validate your R script independent of your ThoughtSpot environment. After you are sure it is free of errors, you can try the script in ThoughtSpot.

How to access R scripts

Users with R script privileges can click the R icon R icon on the toolbar for any search result (answer).

r icon

From here, you have options to write a custom script, or load a pre-built or ThoughtSpot provided script.

r load or write script

Run pre-built R scripts

You don’t have to have a background in statistics or be an R programmer to run R analyses in ThoughtSpot. You can use ThoughtSpot-provided scripts and share the R visualizations with others.

For more on how to run provided scripts, refer to Run pre-built R scripts on answers.

Write your own R scripts in ThoughtSpot

If you know R, you can write your own custom scripts, share them as templates, test and run them on your data in ThoughtSpot, and build up a shared library of R analyses, scripts, visualizations, and Liveboards.

Start with the topic on how to Create and share R scripts to learn more about writing R scripts in ThoughtSpot, including a few particulars on syntax and column bindings.

To learn more about R programming in general, a good place to start is R Project for Statistical Computing. Also, Antony Chen’s blog post on Using R Analysis in ThoughtSpot for Time Series Forecasting is a nice introduction to writing R scripts in ThoughtSpot.

r pinboard examples