Thank you both for the feedback! I'm really happy to be able to empower our budding Clojure Data Science community.
On Wednesday, January 23, 2019 at 7:38:04 AM UTC-8, Chris Nuernberger wrote: > > Great improvements Christopher! The markdown and Jupyter support are > exactly the direction I was hoping for and we really appreciate the work. > > On Wed, Jan 23, 2019 at 1:26 AM Christopher Small <metas...@gmail.com > <javascript:>> wrote: > >> >> Greetings >> >> >> I'm excited to announce the release of oz 1.5.1. >> >> https://github.com/metasoarous/oz >> >> Oz is a simple data visualization library built around Vega & Vega-Lite. >> >> In Vega & Vega-Lite, data visualizations are specified as pure data >> descriptions about how to map properties of your data and interactions to >> aesthetics of a visualization. To find out more about Vega & Oz please >> visit https://github.com/metasoarous/oz. >> >> This release specifically adds some major new features: >> >> * Jupyter notebook support via the Clojupyter & IClojure kernels >> * Export of visualizations and scientific documents to live/interactive >> html files via the `export!` function >> * Load markdown files, with a notation for embedding visualizations as >> code blocks >> * Cljdoc API documentation (https://cljdoc.org/d/metasoarous/oz) >> >> These features, together with those already built into oz (REPL based >> workflow, hiccup support, Reagent components & publishing/sharing API), >> make oz a powerful tool for working with data visualizations and scientific >> documents from within Clojure, no matter the workflow. I hope you find it >> useful. >> >> >> *## Markdown support* >> >> I'd like to specifically illustrate the markdown support feature, as its >> the one I'm most excited to start using myself, as well as the one which >> demands the most explanation. >> >> How many times have you been working on a simple markdown document, and >> realized you wanted to add a data visualization to illustrate a point? >> What did you have to do to get it done? My guess is you had fire up >> another tool, like R's `ggplot`, or Python's `matplotlib`, export a static >> figure, and awkwardly embed it into your markdown document, hoping to God >> you don't have to update it, and go through the ordeal again. >> >> With oz, you can simply embed vega-lite or vega visualizations like this: >> >> # Some markown file >> >> A data visualization: >> >> ```edn vega-lite >> {:data {:values [{:a 2 :b 3 :c "T"} {:a 5 :b 2 :c "T"} {:a 7 :b 4 :c >> "Q"} {:a 3 :b 3 :c "Q"}]} >> :mark :point >> :width 400 >> :encoding {:x {:field "a"} >> :y {:field "b"} >> :color {:field "c"}}} >> ``` >> >> The `load` function parses the markdown file, and uses the `edn >> vega-lite` code block class to determine that the block should be >> interpreted as a Vega-Lite visualization. The fact that `edn` is one of >> the classes here means that your text editor and other markdown processors >> (if you push to GitHub or whatever) will recognize what kind of data it is >> and highlight it appropriately. (Thanks to GH users mpcarolin and yogthos >> for promptly updating their markdown processing libraries to allow for the >> specification of multiple code classes.) >> >> Once loaded, the corresponding document can be immediately viewed with >> the `view!` function, exported to a self-contained html file via `export!`, >> or published online with a shareable link via `publish!`. >> >> This notation allows you to embed as either `json` or `yaml` in lieu of >> `edn`, or `vega` in lieu of `vega-lite`. Moreover, `hiccup` can be >> embedded (possibly with `[:vega ...]` or `[:vega-lite ...]` nodes), for >> when you want more power than Markdown affords, but don't want to resort to >> manually writing html in your beautiful Markdown. >> >> >> *## Jupyter notebook support* >> >> While I personally prefer creating scientific documents from the comfort >> of my favorite text editor & REPL setup, I understand the value of the >> notebook environment. In fact, my first programming language was >> Mathematica, and there's a part of me that holds warm reverie for the >> model. Thus, it is with great pleasure that I announce that Oz can now be >> used as a go-to for those who enjoy using these environments and wish to be >> able to create powerful and interactive data visualizations therein. >> >> This feature would not have been possible without GH users mikeyford, >> keesterbrugge, jtcbrule, cgrand. >> Thank you all for your help initiating and piecing together a solution to >> the problem(s)! >> >> For usage details can be found in the README. >> >> >> *## In closing* >> >> I hope that you find this nexus of features and ideas useful, and that >> you help me make Vega, Vega-Lite & Oz a standard part of the Clojure >> toolkit for data science. >> >> Thanks for your time >> >> Christopher Small >> >> -- >> You received this message because you are subscribed to the Google >> Groups "Clojure" group. >> To post to this group, send email to clo...@googlegroups.com >> <javascript:> >> Note that posts from new members are moderated - please be patient with >> your first post. >> To unsubscribe from this group, send email to >> clojure+u...@googlegroups.com <javascript:> >> For more options, visit this group at >> http://groups.google.com/group/clojure?hl=en >> --- >> You received this message because you are subscribed to the Google Groups >> "Clojure" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to clojure+u...@googlegroups.com <javascript:>. >> For more options, visit https://groups.google.com/d/optout. >> > -- You received this message because you are subscribed to the Google Groups "Clojure" group. 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