New features and improvements in Deedle v1.0

As Howard Mansell already announced on the BlueMountain Tech blog, we have officially released the "1.0" version of Deedle. In case you have not heard of Deedle yet, it is a .NET library for interactive data analysis and exploration. Deedle works great with both C# and F#. It provides two main data structures: series for working with data and time series and frame for working with collections of series (think CSV files, data tables etc.)

The great thing about Deedle is that it has been becoming a foundational library that makes it possible to integrate a wide range of diverse data-science components. For example, the R type provider works well with Deedle and so does F# Charting. We've been also working on integrating all of these into a single package called FsLab, but more about that next time!

In this blog post, I'll have a quick look at a couple of new features in Deedle (and corresponding R type provider release). Howard's announcement has a more detailed list, but I just want to give a couple of examples and briefly comment on performance improvements we did.

Welcome fsharpWorks & upcoming F# events

If you are following me or the #fsharp hashtag on Twitter, you might have already come across a link to fsharpWorks or one of the upcoming F# events organized by fsharpWorks. So, what is fsharpWorks and what are we planning for you?

Stateful computations in F# with update monads

Most discussions about monads, even in F#, start by looking at the well-known standard monads for handling state from Haskell. The reader monad gives us a way to propagate some read-only state, the writer monad makes it possible to (imperatively) produce values such as logs and the state monad encapsulates state that can be read and changed.

These are no doubt useful in Haskell, but I never found them as important for F#. The first reason is that F# supports state and mutation and often it is just easier to use a mutable state. The second reason is that you have to implement three different computation builders for them. This does not fit very well with the F# style where you need to name the computation explicitly, e.g. by writing async { ... } (See also my recent blog about the F# Computation Zoo paper).

When visiting the Tallinn university in December (thanks to James Chapman, Juhan Ernits & Tarmo Uustalu for hosting me!), I discovered the work on update monads by Danel Ahman and Tarmo Uustalu on update monads, which elegantly unifies reader, writer and state monads using a single abstraction.

In this article, I implement the idea of update monads in F#. Update monads are parameterized by acts that capture the operations that can be done on the state. This means that we can define just a single computation expression update { ... } and use it for writing computations of all three aforementioned kinds.

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