Building a Real-Time Dashboard with Node.js and D3.js

In today’s data-driven world, it is essential to have a real-time dashboard that can give us insights into our data in real-time. Building such a dashboard can be challenging, but with the right tools, it is possible to build a dashboard that can give us real-time insights into our data. In this article, we will discuss how to build a real-time dashboard using Node.js and D3.js.

Node.js is an open-source, cross-platform, back-end JavaScript runtime environment that allows developers to create server-side applications using JavaScript. It is known for its fast performance and scalability, making it an ideal choice for building real-time applications. D3.js is a JavaScript library that is used to create dynamic and interactive data visualizations in web browsers.

To build a real-time dashboard with Node.js and D3.js, we will need the following tools and technologies:

  1. Node.js and npm (Node Package Manager)
  2. Express.js (a Node.js web application framework)
  3. (a JavaScript library for real-time web applications)
  4. D3.js (a JavaScript library for data visualization)

Once we have these tools and technologies installed, we can start building our real-time dashboard.

Step 1: Setting up the Project

The first step is to set up our project. We will create a new directory for our project and then initialize it with npm. Here are the steps to do that:

  1. Create a new directory for our project:
mkdir real-time-dashboard
cd real-time-dashboard
  1. Initialize the project with npm:
npm init

This will create a package.json file in our project directory, which will contain information about our project and its dependencies.

Step 2: Installing Dependencies

Next, we need to install the dependencies for our project. We will install Express.js,, and D3.js using npm. Here are the commands to do that:

npm install express d3

Step 3: Setting up the Server

Now that we have installed the dependencies, we can set up the server. We will create a new file called server.js and add the following code to it:

const express = require('express');
const app = express();
const server = require('http').createServer(app);
const io = require('')(server);
const path = require('path');

app.use(express.static(path.join(__dirname, 'public')));

io.on('connection', (socket) => {
  console.log('a user connected');

server.listen(3000, () => {
  console.log('listening on *:3000');

This code does the following:

  1. Imports the required dependencies: Express.js,, and path.
  2. Creates an Express.js app instance.
  3. Creates an HTTP server using the app instance.
  4. Initializes with the HTTP server.
  5. Serves static files from the public directory.
  6. Listens for connections from clients using

Step 4: Creating the HTML and JavaScript Files

Next, we need to create the HTML and JavaScript files that will contain the dashboard. We will create a new directory called public and add two files to it: index.html and app.js.

Here is the code for index.html:

<!DOCTYPE html>
    <title>Real-Time Dashboard</title>
    <script src="/"></script>
    <script src=""></script>
    <script src="app.js"></script>
    <div id="chart"></div>

This code does the following:

  1. Creates a new HTML document.
  2. Includes the and D3.js libraries.
  3. Adds a div with an id of “chart” where the chart will be displayed.

Here is the code for app.js:

const socket = io();

socket.on('data', (data) => {

function updateChart(data) {
  // TODO: Update chart with new data

This code does the following:

  1. Initializes a instance and connects to the server.
  2. Listens for the “data” event and calls the updateChart function when new data is received.
  3. Defines the updateChart function, which will update the chart with new data.

Step 5: Creating the Chart

Finally, we need to create the chart. We will use D3.js to create a bar chart that will display the data in real-time.

Here is the code for the updateChart function in app.js:

function updateChart(data) {
  const margin = { top: 20, right: 20, bottom: 30, left: 50 };
  const width = 960 - margin.left - margin.right;
  const height = 500 - - margin.bottom;

  const x = d3.scaleBand()
    .range([0, width])

  const y = d3.scaleLinear()
    .range([height, 0]);

  const svg ='#chart')
    .attr('width', width + margin.left + margin.right)
    .attr('height', height + + margin.bottom)
    .attr('transform', `translate(${margin.left}, ${})`);

  x.domain( => d.label));
  y.domain([0, d3.max(data, d => d.value)]);

    .attr('class', 'bar')
    .attr('x', d => x(d.label))
    .attr('width', x.bandwidth())
    .attr('y', d => y(d.value))
    .attr('height', d => height - y(d.value));

    .attr('transform', `translate(0, ${height})`)


This code does the following:

  1. Defines the chart dimensions and margins.
  2. Creates an x-axis and y-axis scale using D3.js.
  3. Selects the chart div and appends an SVG element to it.
  4. Defines the domain of the x-axis and y-axis scales based on the data.
  5. Selects all the bars in the chart, binds the data to them, and appends new bars as needed.
  6. Defines the position and dimensions of each bar using the x-axis and y-axis scales.
  7. Appends the x-axis and y-axis to the chart.

Step 6: Sending Data

The final step is to send data to the server so that it can be displayed on the chart in real-time. We can do this by emitting a “data” event from the client to the server whenever new data is available.

Here is an example code snippet for sending data to the server using

const socket = io();

setInterval(() => {
  const data = {
    label: 'Data Label',
    value: Math.floor(Math.random() * 100)

  socket.emit('data', data);
}, 1000);

This code does the following:

  1. Initializes a instance and connects to the server.
  2. Defines a function that generates new data every second.
  3. Emits a “data” event to the server with the new data.

The server will receive this event and broadcast it to all connected clients, who will update their charts in real-time.

And that’s it! With these steps, you can create a real-time dashboard using Node.js and D3.js. Of course, this is just a simple example, and you can customize the chart and data as needed for your specific use case. But this should give you a good starting point for building your own real-time dashboard.