Generally speaking, R language, ggplot2 and Python are used in academia. The most familiar tool for ordinary users is Excel. Commercial products include Tableau, FineReport, Power BI, etc.
D3.js is the most well-known data visualization library today. It is free and open source..
D3 gives developers the ability to create even the most complex charts and graphs. It uses open web technologies — HTML, SVG, and CSS — which is great if you care about cross-platform support (because iOS/Android apps, desktop apps, web browsers, and other such platforms can all run these web technologies). D3 has powerful SVG operation capability. It can easily map data to SVG attribute, and it integrates a large number of tools and methods for data processing, layout algorithms and calculating graphics. It has a strong community and rich demos. However, its API is too low-level. There isn’t much reusability while the cost of learning and use is high.
Note that D3 is designed for modern browsers. It won’t work with old browsers–anything before IE9, and you might have browser compatibility issues. Another thing to consider is that working with D3 will require you to invest some time into learning the D3 API. However, once you learn how to use it, D3 can be an insanely powerful data visualization tool.
Raw bridges the gap between spreadsheets and vector graphics. It’s built on the D3.js platform. If you’re not a programmer, Raw could be the perfect data visualization tool for you.
Raw provides a selection of 16 ready-to-use chart types. Customization is one of the biggest positive aspects of Raw, for it allows you to use your own custom layouts.
Watch this short video to see how Raw works.
TimelineJS is a great tool for creating interactive, visually rich timelines without having to write code. Popular sites like TIME and Radiolab use it frequently to create timelines that display a great deal of information in a small area.
TimelineJS has built-in API support for a variety of data sources like Wikipedia, Twitter, SoundCloud, Vine, Google Maps, and YouTube.
FusionCharts has a collection of over 90 charts and more than 960 maps which can serve the full range of needs of developers and professional data visualization experts. With its support going all the way back to the ancient IE6, browser compatibility is hardly an issue.
FusionCharts is device/platform-agnostic and works easily with both JSON and XML data formats. Here is a sample of their data visualization capabilities. While FusionCharts is slightly heavier on the pocket as compared to some of the other tools in this list, it lets you try all the charts for free before you decide to purchase it.
Tableau Public is capable, easy to use, and free. What more can you want? With a huge arsenal of maps, graphs, and charts, it is a firm favorite for the non-developer audience.
The free version of Tableau attaches a big footer of Tableau branding in the charts you generate; non-commercial customers may be OK with that, but if you aren’t, you can pay to get the cleaner, brand-free versions of the same charts. The company chose not to make its free version feature-poor. Instead, this is the full version of Tableau that's available for free download, with only one caveat: Everything you create with it is public, which means you'll automatically be making it available on the web via Tableau's visualization gallery.
Tableau Gallery is cool enough to warrant a mention all its own because you don't need to download the tool nor use it to benefit from the gallery. Every visualization here can be downloaded into documents and email, or embedded into webpages with code snippets provided by Tableau. Other folks have done tremendous work on some truly impressive data visualizations and Tableau has curated that content and made it available for download. This is a great resource, not only for business people but also for researchers, students, and journalists looking for ways not just to flesh out and beautify their content but to keep it current, too.
Google Charts is user-friendly and compatible with all browsers and platforms. It covers a wide range of data visualization types — from simple line and bar graphs to complex hierarchical tree maps — making Google charts suitable for almost any project.
Check out the gallery that showcases the various charts and visualizations that Google Charts offers.
Part of the Google Marketing Platform, Google Data Studio lets users build multiple views of their data as well as dashboards rather than one-time, publication-ready visualizations. While it follows the Google tradition of requiring somewhat of a learning curve, it's nevertheless not that difficult to use. It's also well integrated with Google Analytics , which can make for quite a powerful pairing—especially since both tools are available in free-to-play versions.
This one purports to transform your spreadsheet, presumably encumbered with some kind of geographical data, into a functioning heat map with just one click. It works with Google Spreadsheets so you'll have to import your Microsoft Excel spreadsheet there if you want to use Openheatmap. But that's a relatively trivial requirement considering the possible results.
Datawrapper is an extremely easy-to-use data visualization tool for plotting interactive charts. All you need to do is upload your data via a CSV file, choose the chart you want to plot, and that’s basically it, you’re good to go! It’s a very popular tool among journalists, often using Datawrapper to embed live charts into their news articles. The fact that it’s a tool of choice for most of the non-techie people out there tells you how easy Datawrapper is to use.
The tool is specifically built for journalists looking to create fast, easily digestible visualizations to accompany their articles; however, it's useful for anyone requiring similiar data views. While there is a paid version that supports the company, there's also a free plan that tops out at 10,000 charts, which should keep many SMB operators happy for quite some time. The tool is entirely web-based, and the website includes not only access mechanics but also an Academy area in which you can take online learning classes on how to use Datawrapper. There's a Gallery area, too, called the River, in which users can upload data and their visualizations for sharing.
This is a well-known chart-creation tool that was made publicly available by financial news website Quartz in 2013. Quartz had developed the tool in-house so its journalists could quickly render numerical data visually to make their stories stand out. Ironically, Chartbuilder isn't very pretty itself and also is not the easiest tool for rank beginners to use. You'll need to understand how to download the tool and activate a Python script to get it running.
But after that, it's simply a matter of cutting and pasting data into the tool (also not pretty but very easy), and then generating a graphic that you can tweak via the tool or via style sheets. The only downside to the tool (aside from a little upfront complexity) is that it doesn't generate interactive visualizations like most of the other tools on this list do. Chartbuilder creates only static charts, though these are very polished, as befits something intended to go from numbers to slick published content in just a few steps.
12. Open Refine
Data transformation is often-overlooked underpinning to a successful data visualization. Transforming data generally refers to the painful (for normal people) process of taking a whole bunch of disparate numbers and turning them into a sleek set of relatable data. That means cleaning data (formatting and error checking), transforming it (changing from one format such as native Microsoft Excel to another, such as XML), and then making it available to external services such as webpages and those BI tools you're using. It is usually a painstaking, eye-watering, brain-bending task,unless you use a data transformation tool such as Open Refine. This tool began life under Google's flag but was rebranded to stand on its own. It's still both free and easy to use so, if you're banging your head against a mountain of mismatched data, then check it out.
If you’re transitioning from Excel and looking for something that doesn’t seem so old-school, you’ve got to give Chartist a look. Created — like all good products — out of frustration with the status quo, it includes a large array of charts that are responsive, animated, and rendered beautifully.
Unlike other bloated apps, Chartist is a small JS library weighing in at 10kb with no dependencies. Oh, and it’s also free. You can check out some nice examples here.
GoodData is a cloud-based data visualization tool that has a special emphasis on providing the fastest connection to your data. It’s relatively easy to adopt as it provides real-time insights that are simple to embed into any applications or workflows currently in use.
Highcharts is free for non-commercial purposes.
Evaluation: Echarts has rich chart types, covering the regular statistical charts. But it is not as flexible as Vega and other chart libraries based on graphic grammar, and it is difficult for users to customize some complex relational charts.
deck.gl is a visual class library based on WebGL for big data analytics. It is developed by the visualization team of Uber. deck.gl focuses on 3D map visualization. There are many built-in geographic information visualization common scenes. It supports visualization of large-scale data. But the users need to have knowledge of WebGL and the layer expansion is more complicated.
FineReport is an enterprise-level web reporting tool written in pure Java, combining data visualization and data entry. It is designed based on “no-code development” concept. With FineReport, users can make complex reports and cool dashboards and build a decision-making platform with simple drag-and-drop operations. FineReport can be directly connected to all kinds of databases, and it is convenient and quick to customize various complex reports and cool dashboards. The interface is similar to that of Excel. It provides 19 categories and over 50 styles of self-developed HTML5 charts, with cool 3D and dynamic effects. The most important thing is that its personal version is completely free.
As an open-source suite of web visualization components that make use of the Python language, Candela emphasizes scalable, rich visualizations created with a normalized API for use in real-world data science situations. This includes components for dynamic rankings and other tools built by teams at Harvard University, the Georgia Institute of Technology, and the University of Washington, among others.
One of the biggest problems in dealing with data is the multitude of sources a single set of data can come from. iDashboards helps to minimize the time and resources required to sift through data, combining data from spreadsheets, databases, and web APIs into a single automated dashboard customized to your needs. iDashboards also emphasizes its intuitive design in order for non-data people to grasp the basics of the free tool.
Processing is a flexible software sketchbook and a language for learning how to code within the context of the visual arts. Since 2001, Processing has promoted software literacy within the visual arts and visual literacy within technology. There are tens of thousands of students, artists, designers, researchers, and hobbyists who use Processing for learning and prototyping.
- » Free to download and open source
- » Interactive programs with 2D, 3D, PDF, or SVG output
- » OpenGL integration for accelerated 2D and 3D
- » For GNU/Linux, Mac OS X, Windows, Android, and ARM
- » Over 100 libraries extend the core software