Anyone used JavaScript for quant research?

This page summarizes the projects mentioned and recommended in the original post on /r/UXResearch

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  • Chart.js

    Simple HTML5 Charts using the <canvas> tag

    I suppose I see many python or R courses doing this. But I’m already quite good with JavaScript, so I don’t see why I shouldn’t use libraries like https://www.chartjs.org/ instead.

  • website

    The Pudding's website (by the-pudding)

    So in summary, I would say knowing both R and JavaScript are very useful. R does have some user interactivity with some of their data viz packages, but if you know JavaScript the ability to edit the front end of your designs with what feels like a scalpel (because everything online is basically html/css and JavaScript) is pretty hard to beat. If you have any questions, or would like more free resources for more specific stuff let me know. I majored in psychology in college and then transitioned into data-related stuff in my MS program because that is where the jobs are. I like the little niche I found in data viz and always love sharing how to learn this stuff. Also I always link data viz from the Pudding because that is where I was first inspired to take interactive data viz seriously, many journalism companies are transitioning into hiring these types of roles as well not just tech. Even though tech pays a lot better obviously. End of rant.

  • SurveyJS

    Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.

  • tidytuesday

    Official repo for the #tidytuesday project

    I still use R for most of my data management and statistics because the language was built for it. Checkout this free book by Hadley Wickham for a quick intro to data science in R. I like using different packages tailormade for whatever analysis I am doing. If you know the name of the analysis you are doing there are plenty of tutorials on how to do it. I did have a couple of statistics courses that taught me the basics beforehand, so you might want to seek out a more theory based statistics book or something like this one. Plus there is a cool online community called Tidyverse Tuesdays that helps you practice wrangling, analyzing, and visualizing with example datasets and share it for critique. I chose to learn R before Python, just because it was more specifically narrowed in on statistics, but I do plan on learning Python eventually for other things (I currently have no opinion on it). R was fairly easy to pick up and there are plenty of blogs, and youtubers (I like Julia Silge she works at R Studio) that run you through projects they create.

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