Being able to come with appealing, interactive visualizations is a large part of a web developers job. In this article, we discuss 9 libraries that can help.
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Since you're reading this, it surely would be no news to you that data visualization has become a very critical part of the IT world today. The huge amount of data being generated by different web technologies needs to be properly refined and visualized for the world to use and gain insights from it.
The advantages of understanding data are tremendous and it leads to making well-informed decisions. The ability of an organization to get their data extracted, cleaned, visualized, and analyzed could very much be the difference between profit or loss.
Before we proceed, here is a list of the libraries I picked out:
It is important to note that this article is not a tutorial. However, links to each library have been added to make the job of learning easier.
What else can you get from a product created by Chinese big-shots Baidu, Inc., if not one with great quality?
Echarts is very useful for visualizing data on web pages. With it, you can create intuitive, customizable, and interactive charts, making interpretation and analysis of data easier.
Documentation is available for this library on its official web page, and you don’t have to freak out about its status of being a Chinese library. It is very well documented in English.
Installing this library is easily done with npm:
npm install echarts --save
Example- Large-sacle scatterplot:
Talking about its flexibility, TauCharts allows for easy access to their API. Giving users the opportunity to seamlessly map and visualize data to get more amazing insights.
It is not just flexible. It also renders the charts pretty fast and is easy to learn.
To install through npm, simply type in:
npm install taucharts
Example - Horizontal line
Simple. Clean. User-friendly.
With Chart.js, you can easily visualize your mixed chart types without hassle, creating responsive web pages by default.
This library allows you to get started with visualizing your data in quick time. Easy to set up, and beginner friendly. With it, you won’t have to get involved in browser compatibility issues, as it supports older browsers.
To install Chart.js using npm:
npm install chart.js --save
Example - Radar
If you are looking to create beautiful, responsive, reader-friendly charts, Chartist is the library to utilize.
Chartist uses SVG to render charts. It also gives the functionality of customizing your charts using CSS media queries and creative animations. You can bring all of your creativity into your charts.
Chartist is notably easy to configure, as well as being easy to customize with Sass. It, however, doesn’t support older browsers like its “sister” Chart.js does.
You can imagine how much perfection you can come up with, as you get to beautify your SVG by styling with CSS and creating all the lovely animations you desire.
This library can also be installed using npm:
npm install chartist --save
There is a lot of information on using this library on its official website.
Example - Pie chart with custom labels
Just like TauCharts, C3 is another very efficient D3-based chart visualization library. As a plus, it allows you to create classes that can easily be customized to personal taste or style.
C3, on the surface, looks like a difficult library to use. However, the moment you get a hold of its techniques, there is no stopping you.
With this charting library, you can update charts even after the first rendering by creating callbacks. It is easy to find your way around using this library, as it also reduces the work to be done by allowing you create reusable charts for your web applications.
To install the C3 chart library using npm, type the following command:
npm install c3
Example - Combination chart
Bring your data to life with HighCharts.js.
It is very much lightweight, as it doesn’t require any plugins. This doesn’t make it any less efficient than the other charting libraries. You can create any chart you can think of, be it the column, bar, pie, or polar chart without putting memory on the line.
For all of its simplicity, HighCharts is also very much compatible with old browsers, so you can pick it if you don’t need to represent data using advanced charting styles.
It can also be installed using npm:
npm install highcharts --save
Example - Highcharts bubbles with radial gradient fill
ReCharts is a chart library built with React and based on the D3 charting library.
It is redefined to make thing easy for React lovers, as you can write charts in your React web applications seamlessly.
Recharts is very much lightweight and renders using SVG elements for creating sensational charts.
It can be installed using npm:
npm install recharts
Recharts doesn’t have a lengthy documentation, as it is straight to the point and also easy to get solutions to issues when you face a brick wall.
Example - Custom content treemap
As much as speed could sometimes be an issue with this library, using it with Fastdom installed makes it much faster.
Example - Simple line chart
jQuery has become a very important tool for web developers over time. With Flot.js, things have just gotten easier.
Flot has developed a huge following overtime and also has a wonderful documentation. Therefore, it is easier to find solutions to problems when you come across a brick wall.
It also gives support to older browsers.
Example - Basic usage
Wrapping It Up
In the end, it would be difficult to choose the best of these libraries, as they are all quality libraries. You could, however, find that some are more difficult to learn, either because of a steep learning curve or due to lack of learning materials on the web. So, it would be best to complement one library with another. There are also lots of other libraries aside from the nine discussed in this article, so just in case you don’t find what you want from this great list of nine you can do some further research.
Not all of these libraries are free though, so it is important you check out their official websites to see the terms and conditions tied to using these tools. This should, however, not stop you from visualizing your data in the most beautiful way possible. Go ahead and represent those numbers with charts.
Published at DZone with permission of Anton Shaleynikov . See the original article here.
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