(Easier) Interactive Data Visualization in React

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If you’re building a dashboard, analytics platform, or any web app where you need to give your users insight into their data, you need beautiful, custom, interactive data visualizations in your React app. But building visualizations hand with a low-level library like D3 can be a huge headache, involving lots of wheel-reinventing. In this talk, we’ll see how data viz development can get so much easier thanks to tools like Plot, a high-level dataviz library for quick & easy charting, and Observable, a reactive dataviz prototyping environment, both from the creator of D3. Through live coding examples we’ll explore how React refs let us delegate DOM manipulation for our data visualizations, and how Observable’s embedding functionality lets us easily repurpose community-built visualizations for our own data & use cases. By the end of this talk we’ll know how to get a beautiful, customized, interactive data visualization into our apps with a fraction of the time & effort!

This talk has been presented at React Advanced 2021, check out the latest edition of this React Conference.

FAQ

The main topic of Anjana Vakil's presentation is interactive data visualization in React.

Data visualization is important because it helps to quickly discover meaning from data, identify patterns, gain insights, and make data-driven decisions.

Observable Plot is a high-level open-source data visualization library that allows users to create meaningful charts quickly and customize them as needed.

Observable Plot was created by Mike Bostock, the creator of the D3 library, along with some teammates at Observable.

The 'grammar of graphics' is a way of describing and systematizing how to create various types of charts from basic concepts, allowing for flexible and customizable visualizations.

Observable Plot is still in a beta phase, and while there is ongoing work on accessibility, it is recommended to check GitHub issues or the Observable forum for the latest updates on accessibility and SSR support.

Anjana Vakil is a developer advocate at Observable and a presenter on interactive data visualization in React.

The slides and links for Anjana Vakil's presentation are available at ObservableHQ.com.

Observable Plot is built on top of D3, which has been optimized over many years for performance, and can handle large datasets efficiently.

You can integrate Observable Plot with a React application using hooks like useRef and useEffect to allow Plot to manipulate the DOM within a React component.

Anjana Vakil
Anjana Vakil
27 min
22 Oct, 2021

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Video Summary and Transcription
This Talk is about interactive data visualization in React using the Plot library. Plot is a high-level library that simplifies the process of visualizing data by providing key concepts and defaults for layout decisions. It can be integrated with React using hooks like useRef and useEffect. Plot allows for customization and supports features like sorting and adding additional marks. The Talk also discusses accessibility concerns, SSR support, and compares Plot to other libraries like D3 and Vega-Lite.

1. Introduction to Interactive Data Viz in React

Short description:

Hi, folks. How's it going? I'm Anjana Vakil, a developer advocate at Observable. Today, I'll talk about interactive data viz in React. Visualizing data can help discover meaning, patterns, and insights. Data viz is valuable for web apps, dashboards, and user insights. It's a wide field, but we can build effective visualizations without learning everything. We'll explore making a reactive data visualization app in React using Observable plot.

Hi, folks. How's it going? It's so good to see your faces. It's so good to see you all here. Oh my gosh. Hi. I'm Anjana Vakil, a developer advocate at Observable and I am beside myself, happy to be here with you all, whether IRL or on the livestream.

What's up, y'all? I am really excited to talk to everybody today about interactive data viz in React. The slides for this presentation and all of the links and everything are up at that URL on observableHQ.com and I will try to tweet that out after the talk as well.

So I am relatively new to the world of data viz as a software developer, JavaScript developer myself, but here's some of the stuff I've been learning about data visualization. So one thing is that when you have a bunch of data, visualizing it, putting it in front of people's eyeballs in an effective way can be the most awesome way to quickly discover actual meaning from that data, see patterns in it, get actual insights, be able to make decisions based on it. That means that data viz is an extremely useful component in a lot of different types of web apps.

So, of course, any kind of dashboard you might be building there's probably going to be a data viz involved. Any time you're trying to give your users insights into their own data on your platforms. Raise your hand if you had to build some kind of data viz in any of your apps. Lots of hands. And I'm sure lots of cyberspace hands as well. So this means it's also a very valuable skill to have on your resume or as part of your developer portfolio. So something worthwhile to learn a little bit about. However, data viz is a wide, wide field. It is something you could spend your entire life and career digging into and getting a dissertation, writing a dissertation in and becoming an expert in and never get to the bottom of. Does that mean in order to build effective visualizations in my apps, I have to, on top of all the regular web and React and JavaScript stuff that I need to know, I have to also learn about statistical analysis and color theory and human visual perception and all of these different things. That sounds really overwhelming and difficult. How can I build a good visualization without having to rededicate my life to learning everything there is to know about data viz.

So it can seem really daunting, it can seem really hard. What hopefully we're going to explore today in the short time we have together is how we can make a non-trivial reactive interactive data visualization app in React without having to learn everything there is to know about data viz. How can I stand on the shoulders of giants and get this data viz up and running as quickly as possible. What we've got here and this is what we're going to build today if the demo gods are with us is a simple visualization of the frequency of different letters in the English language and it's something that I can as a user sort in whatever way I want to see it. So I can sort them by the descending frequency and see it's a little covered up here but the E is the most frequent letter. So this is what we're going to try to build and hopefully see how we don't need to reinvent the wheel to do it. The tool we're going to use for this job is a new relatively new open source DataVis library called Observable plot.

2. Introduction to Plot Library

Short description:

Plot is a high-level library created by the same person who created D3. It allows you to quickly create meaningful and customizable visualizations. Plot employs a grammar of graphics, a way of describing and systematizing chart creation. It provides key concepts like marks, scales, transforms, and facets to create powerful and complex graphs. The library's defaults make layout decisions for you, simplifying the process of visualizing data.

So plot like Observable was created by the same person who created the library D3 if folks have heard of that or encountered that, seeing some nods. So Mike Bostock, who is also a CTO at Observable and some of our other teammates at Observable put together this awesome DataVis library that was released open source earlier this year.

And plot is a very high level library. So it allows you to really quickly get a meaningful chart up and running while at the same time giving you the flexibility to be able to customize and build exactly the right type of visualization that you need for your purposes as opposed to choosing one out of a limited set of options out of the box.

So how it does this is thanks to a very simple and yet very powerful API that is built on the notion of something called a grammar of graphics. So this is a way of thinking about describing and systematizing how we can put together a chart, pretty much any kind of chart we can imagine, from a few basic concepts.

And this is something that's been around in the data vis world for a long time, so we've got, like, experts and tons of decades of research in data vis kind of baked into this grammar of graphics. And then, PLOT itself employs this grammar of graphics, but implements it on top of D3. So we've also got Mike and the rest of the D3 teams, decade of experience building SVG-based visualizations for the web, all baked into this library.

So it's essentially like having a little data vis expert friend in your pocket that can just help you figure out the best chart to build. And so how it does that is by means of a few key concepts. We're not going to go in detail into all of them. You could read all about it. But there are things like marks, which are the visual elements we see on the page. This might be a bar. It might be a line. It might be dots in a scatter plot. There are scales, which are essentially functions that transform the values that I have in my data set, so in my data space, into values in the actual visual representation.

So this might be taking those frequency numbers and turning them into pixels of how high the bar is going to be on the screen. A couple of features we're not going to talk too much about, but are super useful for creating more custom visualizations, things like transforms, so we can do aggregations, like sum, mean, that sort of thing, and facets, which allow you to take a data vis and split it up into smaller subvisualizations that each focus on a subset of the data.

So with these just few concepts, which don't take too long to wrap your head around, you can actually create really powerful and really complex graphs that totally fit whatever your needs are. But at the same time, you can allow the defaults built into Plot to kind of make a lot of the decisions for you, so that you don't need to learn everything there is to know about how to perfectly lay out things on the screen.

So let's take a look at what it actually feels like to write some Plot. Hopefully, folks can read this okay in the back. I'm going to take that as a yes. Okay. So what I've got here is some data about these letters and their relative frequency. So I've got an array of little data objects, datums, that have a letter and a frequency property. To create a Plot, it is a simple call to the Plot method on this sort of capital P Plot object, which is going to create an SVG. And this SVG is super boring.

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