At NDC Oslo 2016, I did a talk about some of the recent new F# projects that are making data science with F# even nicer than it used to be. The talk covered a wider range of topics, but one of the nice new thing I showed was the improved F# Interactive in the Ionide plugin for Atom and the integration with FsLab libraries that it provides.

In particular, with the latest version of Ionide for Atom and the latest version of FsLab package, you can run code in F# Interactive and you'll see resulting time series, data frames, matrices, vectors and charts as nicely pretty printed HTML objects, right in the editor. The following shows some of the features (click on it for a bigger version):

In this post, I'll write about how the new Ionide and FsLab integration works, how you can use it with your own libraries and also about some of the future plans. You can also learn more by getting the FsLab package, or watching the NDC talk..

I was fortunate enough to make it to the Microsoft MVP summit this year. I didn't learn anything secret (and even if I did, I wouldn't tell you!) but one thing I did learn is that there is a lot of interest in data science and machine learning both inside Microsoft and in the MVP community. What was less expected and more exciting was that there was also a lot of interest in F#, which is a perfect fit for both of these topics!

When I visited Microsoft back in May to talk about Scalable Machine Learning and Data Science with F# at an internal event, I ended up chatting with the organizer about F# and we agreed that it would be nice to do more on F#, which is how we ended up organizing the F# + ML |> MVP Summit 2015 mini-conference on the Friday after the summit.

In case you missed my recent official FsLab announcement, FsLab is a data-science package for .NET built around F# that makes it easy to get data using type providers, analyze them interactively (with great R integration) and visualize the results. You can find more on on fslab.org, which also has links to some videos and download page with templates and other instructions.

Last time, I mentioned that we are working on integrating FsLab with the XPlot charting library. XPlot is a wonderful F# library built by Taha Hachana that wraps two powerful HTML5 visualization libraries - Google Charts and plot.ly.

I thought I'd see what interesting visualizations I can built with XPlot, so I opened the World Bank type provider to get some data about the world and Euro area, to make the blog post relevant to what is happening in the world today.

After over a year of working on FsLab and talking about it at conferences, it is finally time for an official announcement. So, today, I'm excited to announce FsLab - a cross-platform package for doing data science with .NET and Mono.

It is probably not necessary to explain why data science is an important area. We live surrounded by information, but extracting useful knowledge from the vast amounts of data is not an easy task. You have to access data in different formats (JSON-based REST services, XML, CSV files or even HTML tables), you need to deal with missing values, combine and align data from multiple sources and then build visualizations (or reports) to tell the right story.

The goal of FsLab is to make this process easier. FsLab combines the power of F# type providers, the efficiency and robustness of Mono and .NET and the high quality engineering of the open-source ecosystem around F# and C#.

There is a bunch of visualization and charting libraries for F#. Sadly, perhaps the most advanced one, F# Charting, does not work particularly well outside of Windows at the moment. There are also some work-in-progress libraries based on HTML like Foogle Charts and FsPlot, which are cross-platform, but not quite ready yet.

Before Christmas, I got a notification from GitHub about a pull request for a simple gnuplot wrapper that I wrote a long time ago (and which used to be carefully hidden on CodePlex).

The library is incomplete and I don't expect to dedicate too much time to maintaining it, but it works quite nicely for basic charts and so I though I'd add the ProjectScaffold structure, do a few tweaks and make it available as a modern F# project.