Data science is the application of statistical analysis, machine learning, data visualization and programming to real-world data sources to bring understanding and insight to data-oriented problem domains. F# is an excellent solution for programmatic data science as it combines efficient execution, REPL-scripting, powerful libraries and scalable data integration.

To contribute to this guide edit this page. These resources are for educational purposes.

Jupyter Notebooks

Integrated Packages

Interactive Charting

Individual Packages

If a resource specific to F# can’t be found, then search for C# instead and adjust the technique appropriately.

Commercial packages


F# and Excel

Excel-DNA is an independent project to integrate .NET into Excel. With Excel-DNA you can make native (.xll) add-ins for Excel using C#, Visual Basic.NET or F#, providing high-performance user-defined functions (UDFs), custom ribbon interfaces and more. Your entire add-in can be packed into a single .xll file requiring no installation or registration:

Sharp Cells is another independent project which integrates F# scripting with Excel. It exposes the scripts as either user-defined functions (UDFs) using Excel’s XLL API or commands using Excel’s COM API. Compilation takes place at runtime allowing rapid iteration of your code and the scripts are embedded with the workbook maintaining single-file portability similar to VBA.

NPOI is .NET version of POI Java project at POI is an open source project which can help you read/write xls, doc, ppt files.

NPOI manipulates the Open Office XML format directly so does not require having Excel installed and do not use Interop. You can read, create, and edit Excel documents using this approach.

There are also some F# versions of Excel functions, useful when migrating code:

F# and R




F# and Python


F# and Mathematica/Wolfram Language