React for Data Visualization
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  • Introduction

Christmas movies at the box office

Christmas movies are the best movies. How much do they make at the box office? Show the power distribution curve with a vertical barchart.

Dataset: Download dataset šŸ—³

My solution šŸ‘‡

How it works āš™ļø

We built this one with React hooks because we can. Not a class-based component in sight āœŒļø

Styled components for styling, D3 for scales and data loading and parsing, hooks to hook it all together.

Loading data with React hooks

I looked around for a good data loading hook. None could be found. So we made our own šŸ’Ŗ

Not that hard as it turns out. You need a dash of useState to save the data you load, a bit of useEffect to run data loading on component mount aaaand ... that's it. Goes in your App function.

function App() {
const [data, setData] = useState(null);
useEffect(
() => {
d3.tsv("/data.tsv", d => {
const year = Number(d.movie.match(/\((\d+)\)/)[1]);
return {
movie: d.movie.replace(/\(\d+\)/, ""),
year: year,
per_year: Number(d.box_office) / (2018 - year),
box_office: Number(d.box_office)
};
}).then(setData);
},
[!data]
);

The useState hook takes a default value, and always returns current state - data - and a setter - setData.

useEffect runs our function on every component render. After committing to the DOM, I believe. We use d3.tsv to load and parse our christmas movie dataset, use a parsing function to transform each row into an object with all the info we need, then call setData when he have it.

Each datapoint holds

  • a movie name
  • the year a movie was produced parsed from the movie name with a regex
  • the per_year revenue of the movie as a fraction
  • the total box_office revenue

Switch display modes with React hooks

Movie box office revenue follows a pretty clear power law distribution. The highest grossing movie or two make a lot more than the next best. Which makes way more than next one down the list, etc.

But how does age factor into this?

Home Alone has had 28 years to make its revenue. Daddy's Home 2 is only a year old.

I decided to add a button to switch modes. From total box_office to per_year revenue. And boy does it change the story. Altho maybe I'm being unfair because how long are theater runs anyway? šŸ¤”

Driving that logic with React hooks looks like this šŸ‘‡

const [perYear, setPerYear] = useState(false)
const valueFunction = perYear ? d => d.per_year : d => d.box_office
// ...
<Button onClick={() => setPerYear(!perYear)}>
{perYear ? "Show Total Box Office" : "Show Box Office Per Year"}
</Button>

A useState hook gives us current state and a setter. We use the state, perYear, to define a value accessor function, and a butto's onClick method to toggle the value.

We're going to use that value accessor to render our graph. Makes the switch feel seamless.

Render

First you need this bit in your App function. It renders <VerticalBarchart> in an SVG, if data exists.

<Svg width="800" height="600" showKevin={perYear}>
{data && (
<VerticalBarchart
data={data}
width={600}
height={600}
value={valueFunction}
/>
)}
</Svg>

That data && ... is a common trick. The return value of true && something is something, return value of false && something is nothing. Means when data is defined, we render, otherwise we don't.

Oh and Svg is a styled SVG component. Gets a nice gif background when showKevin is set to true šŸ˜›

The VerticalBarchart itself is a functional component. We said no classes right?

const VerticalBarchart = ({ data, width, height, value }) => {
const yScale = d3
.scaleBand()
.paddingInner(0.1)
.domain(data.map((d) => d.movie))
.range([0, height])
const widthScale = d3
.scaleLinear()
.domain([0, d3.max(data, value)])
.range([0, width])
return (
<g>
{data.map((d) => (
<React.Fragment key={d.movie}>
<Bar
x={0}
y={yScale(d.movie)}
height={yScale.bandwidth()}
width={widthScale(value(d))}
/>
<Label x={10} y={yScale(d.movie) + yScale.bandwidth() / 2}>
{d.movie}
</Label>
</React.Fragment>
))}
</g>
)
}

We can define our D3 scales right in the render function. Means we re-define them from scratch on every render and sometimes that's okay. Particularly when data is small and calculating domains and ranges is easy.

Once we have a scaleBand for the vertical axis and a scaleLinear for widths, it's a matter of iterating over our data and rendering styled <Bar> and <Label> components.

Notice that we use the value accessor function every time we need the value of a datapoint. To find the max value for our domain and to grab each individual width.

Makes our chart automatically adapt to flicking that perYear toggle šŸ‘Œ

That smooth width transition effect? That's just CSS.

const Bar = styled.rect`
fill: green;
transition: width 500ms;
`

React hooks really do make life easy šŸŽ£

What you learned today

  • the useState React hook
  • the useEffect React hook
  • that it's okay to define D3 stuff in the render method

About the Author

Hi, Iā€™m Swizec Teller. I help coders become software engineers.

Story time šŸ‘‡

React+D3 started as a bet in April 2015. A friend wanted to learn React and challenged me to publish a book. A month later React+D3 launched with 79 pages of hard earned knowledge.

In April 2016 it became React+D3 ES6. 117 pages and growing beyond a single big project it was a huge success. I kept going, started live streaming, and publishing videos on YouTube.

In 2017, after 10 months of work, React + D3v4 became the best book I'd ever written. At 249 pages, many examples, and code to play with it was designed like a step-by-step course. But I felt something was missing.

So in late 2018 I rebuilt the entire thing as React for Data Visualization ā€” a proper video course. Designed for busy people with real lives like you. Over 8 hours of video material, split into chunks no longer than 5 minutes, a bunch of new chapters, and techniques I discovered along the way.

React for Data Visualization is the best way to learn how to build scalable dataviz components your whole team can understand.

Some of my work has been featured in šŸ‘‡

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