In this always evolving AI landscape, researchers and data scientists are often forced to choose between rapid automation and complete control over their analysis. Tools may promise speed, but they tend to limit the adjustment and flexibility to get there. Displayr has always sought ways to limit this assessment.
Well before generative AI became dominant, Displayr supported both pre-built automation and the possibility to add and implement adapted R code. This meant that users were able to analyze and report and report on survey data quickly, accurately and reported in ways that are tailored to their specific needs.
The new Research agent Builds on this, the use of large language models (LLMS) to automate tasks such as cross stabulation, card creation, dashboard structure and strategic comments. Unlike other AI applications, the research agent keeps users under control: any output can be edited and refined, and users can still record adapted R code to expand the functionality.
Here is how it works
The research agent works just like a diligent Junior analyst, but much faster. You give it an example description, background, research questions and the relevant data set. From there, it:
- Generates one Analysis plan– Table per table, built in statistical tests.
- Reads each table, detects patterns and trends.
- Groups findings in themes.
- Evaluates research questions against those themes.
- Draws conclusions and – if requested – gives recommendations.
- Produces one First Draft Report With graphs and tables, ready for refinement.
The result? A coherent, data -controlled report that appears in minutes instead of days.
Ai + r = the best of two worlds
The report produced by the research agent is not necessarily the end of the workflow. The entire document is editable, revisable, verifiable and corrected – so you can easily change the tables behind the visualisations by weighing the data, applying filters, etc.
You can also use R in Displayr to create custom functions and adjust your analysis in the report. This is because Displayr has already installed special servers with R, which means that you do not have to download it to your desktop.
This means that you can use R within Displayr for:
- Simple tables
- R variables
- Custom R -outputs
- Advanced tables
- Just about any form of data analysis
Combining the research agent with custom R code means:
- Any automated output generated by the research agent can be inspected, edited and expanded with your own R code. You can always trace, understand and refine your analysis logic.
- Complex tasks-such as splitting data sets for targeted reporting or building non-standard summaries-being possible thanks to full R integration.
More information about the use of R in Displayr here.
Supercharging AI + R with the AI R -Coder writer
To combine the research agent with adapted R code even faster, Displayr now contains the Ai r Code Writer. Just type a prompt starting with #! Describe in the code -editor what you want, and the AI generates ready -to -run, fully commented R code -complete with explanation.
Because it works directly with the items in your document, the AI R -code writer produces context conscious code for everything, from advanced tables and adapted graphs to data that argues and make up. This means that you can skip the annoying syntax and immediately jump to refining your analysis.
In combination with the research agent, it creates an incredibly efficient workflow: AI draws up your analysis, and by AI -assisted R scripting you can expand, adjust and perfect it in record time.
Ready to see how you can transform your data analysis workflow with Displayr?
Try the Displayr research agent Today and see how quickly you can go from data to decisions.
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