Enhancing Mapping Apps with Observable Plot: A Production Perspective

By Dan McCarey

In my recent work on mapping applications, I’ve had the opportunity to use Observable Plot in production. If you’re building data visualization tools, especially within React applications, Observable Plot deserves a place in your toolkit. Here’s why it stood out for me, and some insights from the experience.

Customizable and Brand-Friendly Visualizations

One of the immediate benefits of Observable Plot is how easy it is to customize visualizations. Branding consistency is often a requirement in production applications, and Observable Plot makes it straightforward to match colors, styles, and other elements to a brand’s aesthetic. Unlike other libraries, which can involve a fair amount of manual tweaking, Observable Plot's concise API lets you define customizations efficiently, without feeling overwhelmed.

Seamless Integration with React

Observable Plot works remarkably well within the React ecosystem. By leveraging useRef and useEffect hooks, integrating plots into React components feels natural and efficient. Here’s a quick example:

import { useEffect, useRef } from 'react';
import * as Plot from '@observablehq/plot';

const MyChart = ({ data }) => {
  const chartRef = useRef(null);

  useEffect(() => {
    const chart = Plot.plot({
      marks: [Plot.barY(data, { x: 'category', y: 'value' })]
    });

    chartRef.current.appendChild(chart);
    return () => chart.remove();
  }, [data]);

  return <div ref={chartRef}></div>;
};

export default MyChart;

This approach keeps components declarative while maintaining control over rendering and updates. Observable Plot’s simplicity means you can focus on the data and visualizations instead of wrestling with boilerplate code.

Iteration Speed: A Visualization Playground

One of my favorite aspects of Observable Plot is how quickly you can iterate on visualizations. Whether it’s a bar chart, line chart, or scatter plot, the library’s minimal syntax encourages experimentation. Need to switch from bars to ticks? It's a matter of changing a single line. The ability to rapidly prototype and tweak charts is invaluable during development.

Less Code, More Clarity

Observable Plot is significantly less verbose than libraries like D3.js. While D3 offers incredible flexibility and control, it often requires writing verbose, low-level code. Observable Plot abstracts away much of that complexity without sacrificing flexibility, so you’ll spend less time coding and more time creating meaningful visuals.

Responsive Scaling: A Feature, Not a Bug

When I first used Observable Plot, its behavior of scaling like an image caught me off guard, especially on mobile devices. Charts don’t dynamically reflow; instead, they scale proportionally with their container. Initially, this felt like a limitation, but the more I thought about it, the more it made sense.

In a world where responsive design often leads to cramped or overly simplified charts, scaling provides a consistent experience across devices. You maintain visual integrity and ensure charts remain legible without requiring extensive responsive logic. It’s a subtle shift in thinking, but it aligns with the principle that charts, like images, should be clear and consistent at any size.

Final Thoughts

Using Observable Plot in production has been a rewarding experience. Its balance of simplicity and power, combined with seamless React integration, makes it a compelling choice for building modern data visualization tools. While it may not replace D3.js for highly complex visualizations, it’s perfect for most use cases where clarity, speed, and customization are priorities.

If you’re looking to elevate your mapping or data visualization projects, give Observable Plot a try. It’s a library that helps you do more with less and brings joy back to creating charts.