Analytics Lab Data Science Tool
Analytics Lab is a flexible coding environment that lets you investigate Morningstar data more deeply than ever to discover new opportunities for investing success.
This Morningstar Direct module combines access to all of our data and research with JupyterLab, an open-source data-science tool, so you can rigorously analyze investments using the Python programming language.
Cutting-edge data science tool
Write code that goes beyond the scope of Direct.
Analytics Lab makes it easy to create customized interactive research that can include analytics, data visualizations, and research narratives.
You can discover new insights and share them with your firm’s Direct users, with the appropriate licensing.
Built for collaboration
Colleagues with Direct can use all the interactive research you create.
Using Analytics Lab requires proficiency in Python, but you don’t need Python skills to interact with research from other users.
You can also analyze a library of Interactive Research created by our analysts and research teams.
Apply your custom analytics across Direct.
Since Analytics Lab is in the Direct ecosystem, clients can access familiar datapoints to create custom calculations in a secure system that transparently outlines their methodology, then add analytics to existing workflows.
Drag, drop, and dig deeper.
We built time-saving features into Analytics Lab to simplify the often-lengthy process of finding data and developing code.
Drag-and-drop capabilities automatically insert Python code from Direct datasets, lists, search criteria, custom-created portfolios, and performance reports, so you know the code is robust and correct.
Powerful data processing at scale
Fast results for 10 lines of code or 10,000.
Analytics Lab’s hosted environment can scale based on computing needs—while analytics run on other platforms can be brought to a standstill when faced with complex calculations, Analytics Lab provides more power on demand to produce quicker results.