How to Create Interactive JavaScript Charts from Custom Data Sets

Charts are a great way of visualizing complex data quickly and effectively. Whether you want to identify a trend, highlight a relationship, or make a comparison, charts help you communicate with your audience in a precise and meaningful manner.

In my previous article — Getting Started with AnyChart: 10 Practical Examples — I introduced the AnyChart library and demonstrated how it is a great fit for your data visualization needs. Today, I want to dig a little deeper and look at AnyChart’s data mapping features which allow you to create beautiful charts from custom data sets with a minimum of fuss.

I also want to look at the many ways you can customize AnyChart to suit your requirements, as well as how you can change the look and feel of AnyChart charts by using themes. There are currently 17 out-of-the-box themes to choose from, or you can create your own. And if you’ve not got the best eye for design, why not buy our book to get a leg up.

As the Head of R&D at AnyChart, I could spend all day talking about this library, but now it’s time to get down to business.

Data Mapping in AnyChart

To facilitate the integration of custom data sources into charting applications, AnyChart has special objects called data sets. These objects act as intermediate containers for data. When data is stored in data sets, AnyChart can track changes to it, analyze it, and work with this data in a more robust and effective manner. In short: interactive JavaScript charts have never been easier!

No matter if you have an array of objects, an array of arrays, or a .csv file, you can use data sets to:

  • ensure full and explicit control over the series created
  • define which column is an argument (x-axis)
  • define which columns hold values for which series
  • filter data
  • sort data

Basics of Data Mapping

The best way to learn how data mapping works in AnyChart is to look at an example. Let’s imagine an array with the following custom data set:

var rawData = [
  ["A", 5, 4, 5, 8, 1, "bad"],
  ["B", 7, 1, 7, 9, 2, "good"],
  ["C", 9, 3, 5, 4, 3, "normal"],
  ["D", 1, 4, 9, 2, 4, "bad"]
];

There’s nothing too wild going on here — this kind of custom data structure is common in a lot of existing applications. But now you want to use this array in AnyChart. With many other charting libraries you would be forced to transform the data to a format that the library can work with. Well, with AnyChart things are a lot simpler — just look what we can do. First, load the array into a data set:

var rawData = [
  ["A", 5, 4, 5, 8, 1, "bad"],
  ["B", 7, 1, 7, 9, 2, "good"],
  ["C", 9, 3, 5, 4, 3, "normal"],
  ["D", 1, 4, 9, 2, 4, "bad"]
];

var dataSet = anychart.data.set(rawData);

And then, once the data has been loaded into the data set, the real magic begins: you can now create so called views. These are data sets derived from other data sets.

var rawData = [
  ["A", 5, 4, 5, 8, 1, "bad"],
  ["B", 7, 1, 7, 9, 2, "good"],
  ["C", 9, 3, 5, 4, 3, "normal"],
  ["D", 1, 4, 9, 2, 4, "bad"]
];

var dataSet = anychart.data.set(rawData);

var view1 = dataSet.mapAs({x: 0, value: 1});
var view2 = dataSet.mapAs({x: 0, value: 2});
var view3 = dataSet.mapAs({x: 0, high: 3, low: 4});
var view4 = dataSet.mapAs({x: 0, value: 5, meta: 6});

You’ll notice that when defining a view, you determine which columns from the original array are included and what names these columns get. You can then use them to create whichever kind of charts you like. For example, here’s how to create a pie chart from the custom data in the 5th column.

Note: AnyChart needs only x and value fields to create a pie chart, but the views also contain a meta field with the data from the 6th column. You can map any number of optional fields and use them as you like. For example, these fields can contain additional data to be shown as labels or as tooltips:

anychart.onDocumentLoad(function() {
  var rawData = [
    ["A", 5, 4, 5, 8, 3, "Bad"],
    ["B", 7, 1, 7, 9, 5, "Good"],
    ["C", 9, 3, 5, 4, 4, "Normal"],
    ["D", 1, 4, 9, 2, 3, "Bad"]
  ];

  var dataSet = anychart.data.set(rawData);
  var view4 = dataSet.mapAs({x: 0, value: 5, meta: 6});

  // create chart
  var chart = anychart.pie(view4);
  chart.title("AnyChart: Pie Chart from Custom Data Set");
  chart.labels().format("{%meta}: {%Value}");
  chart.container("container").draw();
});

And this is what we end up with:

See the Pen AnyChart Pie Chart from Data Set by SitePoint (@SitePoint) on CodePen.

Note: You can find all of the demos in this article as a CodePen collection.

Multi-Series Combination Chart with Custom Data Set

Now, let’s see how we can use the same custom data to create a combination chart with line and range area charts on the same plot. This section is going to be very short since now you know what views are. All you need to do is choose the proper views and create the necessary series explicitly:

anychart.onDocumentLoad(function() {
  var rawData = [
    ["A", 5, 4, 5, 8, 3, "Bad"],
    ["B", 7, 1, 7, 9, 5, "Good"],
    ["C", 9, 3, 5, 4, 4, "Normal"],
    ["D", 1, 4, 9, 2, 3, "Bad"]
  ];

  var dataSet = anychart.data.set(rawData);

  var view1 = dataSet.mapAs({x: 0, value: 1});
  var view2 = dataSet.mapAs({x: 0, value: 2});
  var view3 = dataSet.mapAs({x: 0, high: 3, low: 4});

  // create chart
  var chart = anychart.line();
  // create two line series
  chart.line(view1).name("EUR");
  chart.line(view2).name("USD");
  // create range area series
  chart.line(view2).name("Trend");

  // set title and draw chart
  chart.title("AnyChart: Combined Chart from Data Set");
  chart.container("container").draw();
});

This is what it looks like:

See the Pen AnyChart Combined Chart from Data Set by SitePoint (@SitePoint) on CodePen.

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Source: Sitepoint