Gain insights into creating interactive web data visualizations with D3.js. Learn about SVGs, selections, advanced scatter plots, scales, animations, and interactivity to transform data into meaningful insights.

In this course, you will learn to create your own interactive data visualizations for the web with D3.js, a very popular JavaScript library. 

Starting with the fundamentals, you'll learn about SVG, selections, classes, and styles, as well as displaying data. This will give you the base to start working with more advanced concepts. 

Once you’ve got the basics out of the way, you will start practicing drawing various scatter plots, where you’ll learn all the best practices for creating stunning visualizations.

Lastly, you will dive into scales and one of the more fun parts: adding animation and interactivity.

By the time you finish this course, you will have a powerful new library to add to your resume, and you’ll be able to transform data into meaningful insights.

Master D3.js for Data Visualization

#chart{
  width: 800px;
  height: 800px;
  background-color: #f7f7f7;
  margin: 25px auto;
  position: relative
}

#tooltip {
  text-align: center;
  border: 1px solid #ccc;
  position: absolute;
  padding: 10px;
  background-color: #fff;
  display: none;
}

#tooltip .metric-date {
  text-decoration: underline;
}

.axis {
  font-size: 18px;
  shape-rendering: geometricPrecision;
}


<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>D3 Scatterplot</title>
  
</head>

<body>
  <div id="chart"></div>

  <script src="https://d3js.org/d3.v6.min.js"></script>
  
</body>

</html>

async function draw() {
  // Data
  const dataset = await d3.json('/udata/1kL2GBJw8VB/data-4-1.json')

  const xAccessor = (d) => d.currently.humidity
  const yAccessor = (d) => d.currently.apparentTemperature
  
  // Dimensions
  let dimensions = {
    width: 800,
    height: 800,
    margin: {
      top: 50,
      right: 50,
      bottom: 50,
      left: 50
    }
  }

  dimensions.ctrWidth = dimensions.width - dimensions.margin.left - dimensions.margin.right;
  dimensions.ctrHeight = dimensions.height - dimensions.margin.top - dimensions.margin.bottom;

  // Draw Image
  const svg = d3.select("#chart")
    .append("svg")
    .attr("width", dimensions.width)
    .attr("height", dimensions.height)

  const ctr = svg.append("g") // <g>
    .attr(
      "transform",
      `translate(${dimensions.margin.left}, ${dimensions.margin.top})`
    )

  // Scales
  const xScale = d3.scaleLinear()
    .domain(d3.extent(dataset, xAccessor))
    .rangeRound([0, dimensions.ctrWidth])
    .clamp(true)

  const yScale = d3.scaleLinear()
    .domain(d3.extent(dataset, yAccessor))
    .rangeRound([0, dimensions.ctrHeight])
    .nice()
    .clamp(true)

  // Draw circles
  ctr.selectAll('circle')
    .data(dataset)
    .join('circle')
    .attr("cx", d => xScale(xAccessor(d)))
    .attr("cy", d => yScale(yAccessor(d)))
    .attr("r", 5)
    .attr("fill", 'red')

  // Axes
  const xAxis = d3.axisBottom(xScale)

  const xAxisGroup = ctr.append("g")
    .call(xAxis)
    .style("transform", `translateY(${dimensions.ctrHeight}px)`)
    .classed('axis', true)

  xAxisGroup.append("text")
    .attr("x", dimensions.ctrWidth / 2)
    .attr("y", dimensions.margin.bottom - 10)
    .attr("fill", "black")
    .text("Humidity")
    .style("text-anchor", "middle")


  xAxisGroup.append("text")
    .attr("x", dimensions.ctrWidth / 2)
    .attr("y", dimensions.margin.bottom - 10)
    .attr("fill", "black")
    .text("Humidity")

  const yAxis = d3.axisLeft(yScale);

  const yAxisGroup = ctr.append("g")
    .call(yAxis)
    .classed("axis", true);

  yAxisGroup.append("text")
    .attr("x", -dimensions.ctrHeight / 2)
    .attr("y", -dimensions.margin.left + 15)
    .attr("fill", "black")
    .html("Temperature (&deg;F)")
    .style("transform", "rotate(270deg)")
    .style("text-anchor", "middle")
}

draw()

codemirror

Looking closely, we can see that the axis is going in the wrong direction. The temperature can be read from coldest to warmest. Usually, the y-axis for a scatter plot should be read from top to bottom. The lower a circle is positioned, the colder the temperature. The higher a circle is positioned, the warmer the temperature. We have the exact opposite.

It is not just the axis that is incorrect. The circles are also positioned incorrectly. 

# Understanding the problem

To better understand, let's add an attribute to the `<circle>` elements. We are going to add an attribute to help us debug our problem.

// Draw circles
  ctr.selectAll('circle')
    .data(dataset)
    .join('circle')
    .attr("cx", d => xScale(xAccessor(d)))
    .attr("cy", d => yScale(yAccessor(d)))
    .attr('data-temp', yAccessor)
    .attr("r", 5)
    .attr("fill", 'red')

We are adding an attribute called `data-temp`. The value for this attribute is the `yAccessor` function. We are creating a custom data attribute for storing the temperature of the circle. We will be able to see what temperature a circle represents.

We can use scales to flip an axis since SVG's coordinate system goes from top to bottom for the y-axis.

Overview

SVG Basics

D3 Fundamentals

Drawing a Scatter Plot

Scales

Animations & Interactivity

Even More Charts!

Conclusion

Flipping the Y-axis

Understanding the problem