React Dashboard and Visualizing Data

7 min read

I spent the last six months working on data analytics and machine learning to feed my curiosity and prepare for my new job. It is a challenging mission and I chose to give up for a while on my current web projects to stay focused. Back then, I was coding a dashboard for an automated trading system, powered by an exciting new framework from Facebook : React. In my opinion, Web Components was the way to go and React seemed gentler with my brain than, say, Polymer. One just needed to carefully design components boundaries, properties and states and bam, you got a reusable piece of web to plug anywhere. Beautiful.

This is quite a naive way to put it of course but, for an MVP, it actually kind of worked. Fast forward to last week, I was needing a new dashboard to monitor various metrics from my shiny new infrastructure. Specialized requirements kept me away from a full-fledged solution like InfluxDB and Grafana combo, so I naturally starred at my old code.

Well, it turned out I did not reuse a single line of code. Since the last time I spent in web development, new tools, frameworks and methodologies had taken over the world : es6 (and transpilers), isomorphic applications, one-way data flow, hot reloading, module bundler, …

Even starter kits are remarkably complex (at least for me) and I got overwhelmed. But those new toys are also truly empowering and I persevered. In this post, we will learn to leverage them, build the simplest dashboard possible and pave the way toward modern, real-time metrics monitoring.

Tooling & Motivations

I think the points of so much tooling are productivity and complexity management.

New single page applications usually involve a significant number of moving parts : front and backend development, data management, scaling, appealing UX, … Isomorphic webapps with nodejs and es6 try to harmonize this workflow sharing one readable language across the stack. Node already sells the “javascript everywhere” argument but here, it goes even further, with code that can be executed both on the server and in the browser, indifferently. Team work and reusability are improved, as well as SEO (Search Engine optimization) when rendering HTML on server-side.

Yet, applications’ codebase can turn into a massive mess and that’s where Web Components come handy. Providing clear contracts between modules, a developer is able to focus on subpart of the UI with an explicit definition of its parameters and states. This level of abstraction makes the application much more easy to navigate, maintain and reuse. Working with React gives a sense of clarity with components as Javascript objects. Lifecycle and behavior are explicitly detailed by pre-defined hooks, while properties and states are distinct attributes.

We still need to glue all of those components and their dependencies together. That’s where npm, Webpack and Gulp join the party. Npm is the de facto package manager for nodejs, and more and more for frontend development. What’s more, it can run for you scripts and spare you from using a task runner like Gulp. Webpack, meanwhile, bundles pretty much anything thanks to its loaders. Feed it an entrypoint which require your js, jsx, css, whatever … and it will transform and package them for the browser.

Given the steep learning curve of modern full-stack development, I hope you can see the mean of those tools. Last pieces I would like to introduce for our little project are metrics-graphics and react-sparklines (that I won’t actually describe but worth noting for our purpose). Both are neat frameworks to visualize data and play nicely with React, as we are going to see now.

Graph Component

When building components-based interfaces, first things to define are what subpart of the UI those components are. Since we start a spartiate implementation, we are only going to define a Graph.

// Graph.jsx

// new es6 import syntax
import React from 'react';
// graph renderer
import MG from 'metrics-graphics';

export default class Graph extends React.Component {

  // called after the `render` method below
  componentDidMount () {
    // use d3 to load data from metrics-graphics samples
    d3.json('node_modules/metrics-graphics/examples/data/confidence_band.json', function(data) {
    data =, 'date');
        title: {this.props.title},
        data: data,
        format: 'percentage',
        width: 600,
        height: 200,
        right: 40,
        target: '#confidence',
        show_secondary_x_label: false,
        show_confidence_band: ['l', 'u'],
        x_extended_ticks: true

  render () {
    // render the element targeted by the graph
    return <div id="confidence"></div>;

This code, a trendy combination of es6 and jsx, defines in the DOM a standalone graph from the json data in confidence_band.json I stole on Mozilla official examples.

Now let’s actually mount and render the DOM in the main entrypoint of the application (I mentioned above with Webpack).

// main.jsx

// tell webpack to bundle style along with the javascript
import 'metrics-graphics/dist/metricsgraphics.css';
import 'metrics-graphics/examples/css/metricsgraphics-demo.css';
import 'metrics-graphics/examples/css/highlightjs-default.css';

import React from 'react';
import Graph from './components/Graph';

function main() {
    // it is recommended to not directly render on body
    var app = document.createElement('div');

    // key/value pairs are available under `this.props` hash within the component
    React.render(<Graph title={Keep calm and build a dashboard}/>, app);


Now that we defined in plain javascript the web page, it’s time for our tools to take over and actually build it.

Build workflow

This is mostly a matter of configuration. First, create the following structure.

$ tree
├── app
│   ├── components
│   │   ├── Graph.jsx
│   ├── main.jsx
├── build
└── package.json

Where package.json is defined like below.

  "name": "react-dashboard",
  "scripts": {
    "build": "TARGET=build webpack",
    "dev": "TARGET=dev webpack-dev-server --host --devtool eval-source --progress --colors --hot --inline --history-api-fallback"
  "devDependencies": {
    "babel-core": "^5.6.18",
    "babel-loader": "^5.3.2",
    "css-loader": "^0.15.1",
    "html-webpack-plugin": "^1.5.2",
    "node-libs-browser": "^0.5.2",
    "react-hot-loader": "^1.2.7",
    "style-loader": "^0.12.3",
    "webpack": "^1.10.1",
    "webpack-dev-server": "^1.10.1",
    "webpack-merge": "^0.1.2"
  "dependencies": {
    "metrics-graphics": "^2.6.0",
    "react": "^0.13.3"

A quick npm install will download every package we need for development and production. Two scripts are even defined to build a static version of the site, or serve a dynamic one that will be updated on file changes detection. This formidable feature becomes essential once tasted. But we have yet to configure Webpack to enjoy it.

var path = require('path');
var HtmlWebpackPlugin = require('html-webpack-plugin');
var webpack = require('webpack');
var merge = require('webpack-merge');

// discern development server from static build
var TARGET = process.env.TARGET;
// webpack prefers abolute path
var ROOT_PATH = path.resolve(__dirname);

// common environments configuration
var common = {
  // input main.js we wrote earlier
  entry: [path.resolve(ROOT_PATH, 'app/main')],
  // import requirements with following extensions
  resolve: {
    extensions: ['', '.js', '.jsx']
  // define the single bundle file output by the build
  output: {
    path: path.resolve(ROOT_PATH, 'build'),
    filename: 'bundle.js'
  module: {
    // also support css loading from main.js
    loaders: [
        test: /.css$/,
        loaders: ['style', 'css']
  plugins: [
    // automatically generate a standard index.html to attach on the React app
    new HtmlWebpackPlugin({
      title: 'React Dashboard'

// production specific configuration
if(TARGET === 'build') {
  module.exports = merge(common, {
    module: {
      // compile es6 jsx to standard es5
      loaders: [
          test: /.jsx?$/,
          loader: 'babel?stage=1',
          include: path.resolve(ROOT_PATH, 'app')
    // optimize output size
    plugins: [
      new webpack.DefinePlugin({
        'process.env': {
          // This has effect on the react lib size
          'NODE_ENV': JSON.stringify('production')
      new webpack.optimize.UglifyJsPlugin({
        compress: {
          warnings: false

// development specific configuration
if(TARGET === 'dev') {
  module.exports = merge(common, {
    module: {
      // also transpile javascript, but also use react-hot-loader, to automagically update web page on changes
      loaders: [
          test: /.jsx?$/,
          loaders: ['react-hot', 'babel?stage=1'],
          include: path.resolve(ROOT_PATH, 'app'),

Webpack configuration can be hard to swallow at first but, given the huge amount of transformations to operate, this style scales very well. Plus, once setup, the development environment becomes remarkably productive. To convince yourself, run webpack-dev-server and reach localhost:8080/assets/bundle.js in your browser. Tweak the title argument in main.jsx, save the file and watch the browser update itself. We are ready to build new components and extend our modular dashboard.


We condensed in a few paragraphs a lot of what makes the current web ecosystem effervescent. I strongly encourage the reader to deepen its knowledge on those matters and consider this post as it is : an introduction.

Web components, like micro-services, are fun, powerful and bleeding edges. But also complex, fast-moving and unstable. The tooling, especially, is impressive. Spend a hard time to master them and craft something cool !

About the Author

Xavier Bruhiere is a Lead Developer at AppTurbo in Paris, where he develops innovative prototypes to support company growth. He is addicted to learning, hacking on intriguing hot techs (both soft and hard), and practicing high intensity sports.


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