Data visualization is the means for making graphic representations of data and information. This includes bar graphs, charts, heat maps, and pie charts.
Data viz is a common abbreviation for data visualization. It is an important tool in extracting the story behind the numbers. Many people prefer a visual representation as it helps them to understand the information better and faster. So, data visualization makes data look more attractive and easier to consume.
It is clear then, that data visualization requires a scientific and an artistic side. And there are many digital tools that help you to balance both visualization elements. Finding the tools that represent your data in the right way can be a challenge.
This article reviews some of the best data visualization JavaScript libraries that you can find on the internet.
FusionCharts Suite
The first on this list of data visualization JavaScript libraries is FusionCharts Suite. It contains various tools for compiling charts and maps. In fact, there are more than 100 charts and 2,000 maps for immediate use. It is one of the most complete data visualization libraries available.
By default, FusionCharts uses HTML5 and SVG for rendering maps and charts. It still allows users to export their work to Flash which is useful for older Actionscript3-dependant browsers.
This JavaScript data visualization library offers a wide range of customization options. You can select themes, adjust tip texts, change axis labels, and much more.
Applications are endless with the many options that FusionCharts offers. You can use it to display real-time data and even build executive data dashboards.
Recharts
Recharts, built on React components, let you change charts and add interactive elements.
This lightweight JavaScript data visualization library uses SVG map rendering. This tool is easy to work with and comes with comprehensive documentation.
You can start building your charts with one of the various examples and personalize them. It works best for making static customized charts. There are options to add tooltips and other labels.
It is a bit slow when it comes to building animated charts and working with large datasets. Still, it works great for most applications.
Some useful elements that you can add to your charts are
- Data callouts
- Data labels
- Data plots
- Data ranges
- Multiple panes
- Rendered objects
Google Charts
Google Charts example created with wpDataTables
Google Charts falls into the category of open-source JavaScript data visualization libraries. It is very robust despite its simplicity.
Google Charts has extensive charting libraries, and you can find complete information about the API. With these outstanding features, you get the sense that the best JavaScript experts have worked on it.
You can create some 29 basic charts, and there is help for those with little JavaScript experience. You can display your live data using one of the many interactive charts. These are some of the charts that you can select:
- Bar charts
- Doughnut charts
- Pie charts
- Scatter charts
These options are only the starting point to all that you can customize.
Chart.js
Chart.js example created with wpDataTables
Creating data visualizations is easy with Chart.js. This simple data visualization library lets you create basic graphics, like line and bar charts. Large organizations such as New York Times and Google use it to create their infographics from large datasets.
It only supports HTML5, but it is enough to display in standard web browsers. The charts thus don’t need Flash or other plugins to work.
To use Chart.js you don’t need extensive knowledge of SVG elements or other D3 techniques. The idea behind this data visualization library is to create beautiful charts quickly and easily.
D3.js
D3.js calls itself the golden standard of JavaScript data visualization. Many developers have used D3.js as a basis for their data visualization tools.
A major advantage is that it offers an ample selection of visualization coding languages, such as CSS, HTML, and SVG. It provides more flexibility for you when it comes to data visualization.
On the downside, D3.js is not very easy to work with and has an intimidating learning curve. There are also no charts provided in their base library. There is a vast community that supports and answers questions.
A search on the internet reveals that there are several data visualization JavaScript libraries based on D3.js, like C3js and react-d3. They will render similar charts to D3.js, like area, bar, line, pie, and scatter.
three.js
Three.js is a responsive data viz library and API. It is one of the best JavaScript data visualization libraries for making 3D and animated graphics for web browsers that use WebGL.
GPU-quickened 3D animations in combination with JavaScript are the workhorse of three.js. It can thus render images in web browsers without having to rely on third-party program plugins. This WebGL approach makes three.js one of the most popular data visualization libraries.
Below is a small list of three.js’s most prominent features:
- Animation:
- Armatures
- Forward and inverse kinematics
- Keyframe
- Morph
- Cameras
- Controllers
- FPS
- Orthographic
- Path
- Perspective
- Trackball
- Effects
- Anaglyph
- Cross-eyed
- Parallax barrier
React-vis
The next example comes from an unexpected source, and yet, it is the largest data visualization library supporter in the world, Uber.
With React-vis, Uber offers a clean and simple data visualization library. The documentation provides excellent support for those who need it. Making an area, bar, line, pie, or tree graph is simple and easy.
An advantage is that you don’t need experience with D3.js or a similar library to work with React-vis. It has plenty of simple tools and chart components, like the X-Y axis, to make it accessible to anyone. React-vis is a great choice if you want to work with Bit. All in all, it is simple, robust, and flexible.
Chart.xkcd
The way Chart.xkcd renders charts is unique. Instead of making straight computerized graphs, it makes your charts with a hand-drawn appearance. Despite its uniqueness, it is still very easy to work with, and it does most of the coding for you.
With Chart.xkcd you can make various basic charts, like bar, line, pie, and radar charts. Each of these chart types has its own customization options to change the way they look. If you prefer, you can disable the sketchy and cartoony look and go for something more traditional.
Victory
Victory is one of the data visualization tools for React or React Native. It renders your data in a graphical format and allows you to customize the labels and appearance. Victory has made sure that the steps to change important elements, like labels and axes, are very simple. This data visualization library is very convenient to use.
The charting process is even simpler thanks to cross-platform applications and other elements. The powerful, yet flexible, library is not too complicated as it does not rely heavily on coding. Its purpose is to allow people to make interesting and accurate data visualizations.
Deck.gl
The main advantage of Deck.gl is that it supports large datasets. Like previously mentioned examples, it uses WebGL and has outstanding performance.
The developers of Deck.gl used a layered approach. Before rendering, the library assigns positions, colors, and other characteristics to each element. The advantage is that it can render different layers with the same data. This makes adjusting the appearance and modifying labels very straightforward. All layers, like columns, contours, and bitmaps, went through extensive testing and all work well.
The WebGL basis allows for high-level performance because it uses the device’s GPU.
Apache ECharts
The next example is free and open-source. Apache ECharts is simple to use, and it’s easy to add interactive chart elements. Its main purpose is to make charts for use on interactive web pages. This data visualization library provides various options for chart customization.
The library includes over 20 chart types that you can use to display your data. There are also many other components that you can use wherever you want.
It also allows you to do some simple data analysis on your datasets. These include clustering, filtering, and regression analysis. Apache ECharts enables you to make a more in-depth analysis of your numbers.
Two final things to mention are the ability to process large datasets and the English documentation.
MetricGraphics.js
MetricsGraphics.js is one of the many data visualization JavaScript libraries that uses D3 as a base. It expands on the parent library by adding upgraded picturing and time-arrangement information. Its use is straightforward, and its design is tightly organized.
This responsive library offers bar diagrams, histograms, line graphs, scatterplots, and more. Also, you will find essential straight relapse and floor covering plots.
MetricGraphics.js aims to remove some of the complications of data visualization. This tool to visualize data is practical and efficient.
Highcharts
Highcharts example created with wpDataTables
This next JavaScript library is one of the most established ones on the list. It uses technologies that are common to most modern browsers including on mobile devices which makes it very responsive. There is no need for users to install a third-party plugin like Flash to perform.
It offers most of the most common chart types and elements:
- Angular gauges
- Bar charts
- Error bars
- Gantt charts
- Map-based charts
- Pie charts
- Stock charts
- Waterfall
- And more
Non-commercial users can use Highcharts for free. This includes use for personal projects, educational institutions, non-profit organizations, and charities.
Raphaël
Raphaël is a vector drawing library for making charts. There are various sub-libraries available for download. You can download the one you want for your project.
The main library, g.raphael.js, is very small and so are the sub-libraries. Despite its lightweight, it is very powerful in making beautiful data visualizations.
VX
This charting library is simple and contains several reusable React components. Like other libraries, VX uses D3 to visualize data and React to add other effects.
The philosophy behind VX is that it should be modular and contain elements that you can use again and again. That keeps the size of the library to a minimum. Still, the results are unique charts, and the visual freedom is in the hands of the users.
Behind its simple appearance, it uses powerful D3 calculations and algorithms. Yet, you don’t need to make your charts look like D3. VX contains enough components to hide the use of D3 and React.
ApexCharts
ApexCharts example created with wpDataTables
The next example from the data visualization realm is ApexCharts. It uses React and Vue.js to render beautiful charts in SVG format. The data visualizations look great on any device, and you’ll find library support in the form of ample documentation. It does slow down with larger datasets, so keep that in mind if you are considering ApexCharts.
This data viz tool works with most modern browsers, such as
- Chrome
- Firefox
- Internet Explorer 8 and higher
- iOS
- Opera
- Safari
This JavaScript data visualization library is new on the market, and there will be updates. Have a look at this option if you want interactive visualization designs and responsiveness.
Flexmonster
You can use Flexmonster straight in your web browser. The user interface lets you view and edit your data and chart right away. You can import external data and you can establish connections with different data sources.
Other compatibilities include
- Amazon Redshift
- Google Datastore
- MySQL
- PostgreSQL
Flexmonster components include charts, dashboards, maps, and tables. You can add any of them to your web apps to process data.
React Virtualized
As the name suggests, React Virtualized uses React segments for rendering charts. CommonJS, ES6, UMD, and Webpack 4 are added elements. You need to establish the react-dom to rule out clashes with other variants.
Sigma.js
Sigma.js is perfect if you want to include thousands of edges and nodes in your data visualizations.
WebGL forms the basis for rendering graphics. Sigma.js has that as an advantage over canvas and SVG when it comes to creating large graphs. Graph customization, however, becomes more difficult. You can use this data visualization tool inside your React applications.
Sigma.js is perfect for rendering large graphs, with thousands of nodes and edges. If your renderings have fewer than a thousand nodes and edges, it is better to use D3.js. That will make customizing your charts more manageable.
TradingVue.js
TradingVue.js is one of the best JavaScript data visualization libraries with hackable features. You can make almost any kind of drawing over the candlestick charts which is great for making trading applications and custom indicators.
TradingVue.js attaches screen coordinates to your data. You will see them on the screen. The library does all the hard work behind the scenes, like scaling, scrolling, and reactivity. In the meantime, you can zoom and scroll as much as you want.
C3js
Again, C3js has a core of D3.js. D3.js does all the heavy graph rendering work. C3js is, in other words, a D3.js wrapper that includes all the code that you need to make charts.
The advantage that C3js has is the flexibility in customizing the charts. The element classes let you change each element to the extent you want. You can add your own stylings and other functionalities with the power of D3.js.
C3js still offers a lot of flexibility through callbacks and APIs. You can still make changes after the rendering of the chart if you want.
JSXGraph
A team at the University of Bayreuth in Berlin created JSXGraph. This standalone charting library can plot complicated geometric figures and data. It is ideal for showing differential equations, Bezier curves, and many other complex shapes.
You can add animation to your graphs so that people can move them around. There are interactive components that you can use, like sliders for changing variables. There are many basic chart types that you can use as the basis for your representations.
Final Words on Data Visualization JavaScript Libraries
This list is aimed at helping you to understand more about data visualization JavaScript libraries. This knowledge will help you decide which of these data viz libraries is best for you.
As you noticed, there are premium and free libraries. What is best for you depends on your graph-rendering needs. Besides your output needs, you need to think of how to best enter your information into the library.
The number of choices may seem overwhelming, but that only reflects the need for good data visualization tools. The good thing for you is that these tools get better and better all the time.
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