What are the best open-source data visualization tools?

How is data visualized?

Data visualization is achieved by gathering raw data from multiple sources, compiling it, and then transferring that into a unified format. Once everything is in one place and a single form, you can clear it, organize it, filter it, and modify it for presenting a specific point. To all of these things, you are likely going to rely on a data visualization tool that has all of these features, which allow you to import and manipulate data.

What are data visualization tools?

As mentioned, data visualization tools are software that allows you to organize and visually enhance how information is displayed. However, there are multiple tools out there, and they vary in terms of functionalities, integrations, complexity, and prices.

Let’s take a tool like Whatagraph, for example. It is primarily aimed at businesses that want to monitor marketing efforts, generate reports for sale rates, finances, user-engagement, or at companies that provide these services and need reports for their clients. You can draw these conclusions based on the features it has and integration capabilities with other platforms. Moreover, it has a user-friendly interface that is easy to navigate and aimed at those who don’t have a background in coding.

However, different businesses have different data visualization needs and use tools specifically tailored for their model. These custom made models are typically paid software as someone went above and beyond to adapt it for a specific group and make it easy to use. That being said, there are open-source tools that won’t require any purchase to use them. In other words, if you wish to become proficient in data visualization, these tools would be a good starting point.

Best Open-Source Data Visualization Tools

Candela

Here is a perfect example of an open-source solution with a wide variety of data visualization features. However, to use it, you will need to know how to integrate it into your platform. Candela has a detailed guide on how to handle Python, JavaScript, or R integration. So, if you know someone who can help you with this, Candela will be an excellent tool to master so that you can create bar charts, line charts, geo dots, boxplot, etc.

Charted

Charted is a straightforward and fast solution. If you need to create bar or line charts, this is probably the easiest way to go about it. All you need to do is have your csv.file or a link to a Google Sheet that you can insert into Charted. Once you press GO, the tool will automatically generate the chart. The dev team that created Charted stated they designed around three principles:

1. It’s not a formatting tool;
2. It does not transform the data;
3. It does not store data.

As they were thinking within this framework, it’s easy to see how they created a widely accessible and easy to use platform. However, bear in mind that a lot of utility and flexibility was lost along the way.

RawGraphs

RawGraphs is somewhat similar to Charted as it is aimed at casual users, but it also caters to advanced users or data visualization veterans. One reason why RawGraphs is superior to Charted is the toolbox. Users can create different types of charts (pie, line, bar), infographics, diagrams, etc. All you have to do is just copy/paste data, upload the document or once again provide a link.

Furthermore, you can learn new things by going through their tutorials and find out how to utilize the features of the platform entirely. If you like RawGraphs, you can even donate to the developers as they are giving it for free because this way, you help them make the product even better.

Datawrapper

Datawrapper has been around for some time now, from 2011 to be precise. It has packages for paying customers, but it offers a free version as well, which is why it’s on the list. The primary user group is most likely journalists, but it seems that researchers or data experts also rely on Datawrapper. Also, you don’t need any skill in coding to use Datawrapper, it’s pretty much like Charted and RawGraphs in that sense, as all you have to do is copy and paste the content. Anything that you create on Datawrapper can be published and embedded on a specific website. Once again, there is an array of charts that you can make using Datawrapper, so feel free to try it out.

Chartist.js

In the unlikely event, you did not know “.js” implies that the software comes from the JaveScript library. Chartist.js is excellent for visualization of data as it has an arsenal of customization options. The tool might lack diversity when it comes to graph types, but it makes up for it in utility and quality. Just to put things into perspective, Chartist.js allows you to create animations using SVG or scalable vector graphics. This is regarded as a top tier tech when it comes to animations, and you will have a blast figuring out all the ins and outs of this free and open-source data visualization tool. Just for the heads up, you might come across some compatibility issues, depending on the browser you are using.

Leaflet

So far, the covered tools were mainly used for creating charts, but that’s not the only and the most efficient way to visualize data depending on your data analysis and the type of business you might want to create maps rather than chats, which is where Leaflet comes in handy. With Leaflet, you get multiple mapping layers features and interactions, which makes it easy for you to create a detailed representation of your findings. If you feel that it’s troublesome to navigate the interface, you can always go through the tutorials and even go through advanced training in case you wish to improve your skills in Leaflet.

Polymaps

As we are on the topic of maps, let’s go over another top player from JavaScript corner Polymaps. With Polymaps, you can generate interactive and dynamic maps using your web browser. As this tool leverages CSS and SVG, you can look forward to impressive feats of visualization, once you become a pro. You can do street layering, create maps detailing population density, migration patterns, anything you want to present on a plan.

OpenHeatMaps

Just in case working on data visualization within a browser of the JavaScript framework isn’t your cup of tea, then OpenHeatMaps has you covered. Once again, the data is fed to the system through document upload (CSV, or excel) or by adding the Google Sheets link. Once you do that OpenHeatMaps will generate the map automatically,

The software can also be used as a JQuery plugin in case you wish to add mapping functionality to a specific website. So, if your main goal is to allow customers to find your physical store or office when they visit your site, OpenHeatMaps can be helpful.

D3.js

This is another open-source javascript solution, created to utilize modern browsers fully. D3.js represents Data-Driven Documents, and visualization is achieved through the use of HTML, CSS, and SVG. When it comes to functionality, design creativity, and features D3 is maybe one of the best free and open-source software, however, it’s not suited for casual users. If you wish to learn how to use D3, you will need knowledge in coding, so if this is a deal-breaker, then you’ll have to choose something else from the list. On the other hand, you can use the tool to create stellar graphs and stand out from the crowd, so if an impressive design is your top priority, D3 is perfect.

Plotly

Plotly is an excellent tool for building analytics apps, and many famous brands rely on its services. So, there is a proprietary version of Plotly, and there is also an open-source version that you can use. Plotly is mainly used to create interactive analytic dashboards and apps, as well as online chats. The open-source libraries are available through JavaScript, R, and Python, while primary intelligence tools consist of the dashboard, slide decks, charting, and SQL client. Of course, the paid version gives you more features like the ability to share data and collaborate with your team online.

DyGraphs

DyGraphs is yet another open-source software for data visualization with a JavaScript-based library. It is supposed to help you organize and process dense sets of data, and it also offers support for error bars. To give some clarity on that end, error bars represent the variability of data or the degree of uncertainty in your measurements. In other words, you can see how reliable are the charts that you created, which is useful for any analytic data app. Furthermore, there are many tutorials you can go over so that you can get started and be up to speed with how the tool functions.

Google Charts

Lastly, let’s not forget about Google Charts. It is also a free tool that allows you to create interactive charts by supplying relevant information. It has an extensive library of different data visualization methods, pie, bar, donut, organization, and other tables, along with maps, timelines, world trees, etc. It’s readily available, and you can always check it out, so make sure to give it a go. As this is Google’s product, you can always be sure it will receive the support it needs.

Hopefully, you know a bit more about data visualization, or at least you have an idea of what skills are necessary to get better at it. There are multiple open-source tools here for visualization of data, so one of them is bound to aid you in your endeavors.