Data visualization (also known as dataviz) tools give a visual meaning to datasets. It helps to better represent complex data and datasets to make it more usable by viewing patterns and trends across all of the data. It also displays data that stands out from the rest to identify outliers of data.
Choosing which data visualization tool to use largely depends on the type of data being worked with and the objective for using the data with other factors to consider when choosing a free data visualization tool. Since the visualization platforms below are free and/or open-source, there are options to evaluate which open-source visualization technique represents the data in the best way. It could be an interactive map to line and graph charts to histograms.
Please note that many of these tools are updated, maintained, or have additional contributions to it on GitHub beyond what you may see on the visualization tool site or video.
List of 25 Free and Open Source Visualization Tools:
According to Candela it is “an open-source suite of interoperable web visualization components for Kitware’s Resonant platform. Candela focuses on making scalable, rich visualizations available with a normalized API for use in real-world data science applications.”
Learn more about Candela
2. Chartist. js
Learn more about Chartist.js
Colorbrewer version 1.0 was funded by the NSF Digital Government program during 2001-02, and was designed at the GeoVISTA Center at Penn State and this redesigned version 2.0 was donated by Axis Maps LLC. Although it’s not a standalone data visualization tool, it is used as a diagnostic tool for evaluating the individual color schemes to be used on a difficult map.
Learn more about Colorbrewer
Cytoscape is a Java-based open-source platform for bioinformatics analysts. It’s used to support biology, genomics, and proteomics data. It can create visual maps, can integrate global datasets, and load molecular and genetic data and different formats.
Learn more about Cytoscape
Learn more about D3.js
Datawrapper is used to create interactive charts, maps, and tables that can be available on all devices. On mobile, it is fully responsive. It will transform data so it can be used on a website, social media, or a file (HTML, PNG). A PDF or SVG file are paid options. An API is also available to automate the process.
Learn more about Datawrapper
Learn more about Dygraphs
8. Ember Charts
Ember Charts is built on Ember.js and d3.js. It allows users to create the following charts: time series, pie, scatter, stacked pie, horizontal bar, vertical bar. It’s customizable with several charting features.
Learn more about Ember Charts
Learn more about Flot
Gephi and an open graph viz platform that is used mostly by data analysts and scientists. It offers poster creation, biological network analysis, social network analysis, link analysis, and exploratory data analysis. It looks a lot like Photoshop ™ but is used for graphing data and currently runs on Windows, Mac OS X, and Linux. The purpose is to spot patterns, come to better data conclusions, and locate outliers.
Learn more about Gephi
11. Google Charts
Google Charts is free and makes it easy to show live data. It’s integrated into Google Docs to transform data into interactive visual data by just hitting the Insert option in Sheets, Docs, and Slides. With over 30 chart types, there are many options to choose from and a simple interface that anyone can use.
Learn more about Google Charts
Google Data Studio digs deeper into Google Graphs as an easy drag and drop creation process. This free tool transforms data into data visualizations that are simple to read creates reports that are customizable. It is also easy to share and collaborate by granting access.
Learn more about Google Data Studio
Learn more about Kibana
Learn more about LeafletJS
OpenRefine (formerly Google Refine) is an open-source application written in Java to refine and clean up data then transform it into a usable format. It will find systematic errors, inconsistencies, and even duplicates.
Learn more about OpenRefine
Palladio was created by Developed at CESTA’s Stanford Humanities + Design lab. It’s a web-based visualization tool that uses data from networks and maps. Used mostly for data that has many attributes, is structured, and information is needed regarding time and space relationships.
Learn more about Palladio
ParaView is an open-source multi-platform visualization tool written in Python, Fortran, C, and C++. It creates scientific visualizations using qualitative and quantitative methods.
Learn more about Paraview
PathVisio is a Java-based pathway editor, analysis, and visualization software. It allows drawing, editing, and analyzing biological pathways. There are currently 13 plugins to use with PathVisio.
Learn more about PathVisio
Learn more about Plotly
Learn more about Polymaps
RawGraphs is an open-source visualization tool used to display complex data in an understandable format. It was created to bridge the gap between various spreadsheets and vector graphics editors. Easy to upload data and just choose a visual model then start mapping and customizing. This is just one of a series of tutorials for RawGraphs.
Learn more about RawGraphs
22. Tableau Public
Tableau Public allows the transformation of data into insights. It allows users to visualize and then publish their data to the web.
Learn more about Tableau Public
Timeline is used to make amazing visual interactive timelines. Easy to use for anyone to use with just a basic spreadsheet in literally 4 steps. There is an option to create custom installations for those with JSON skills.
Learn more about TimelineJS
VTK (The Visualization Toolkit) is mostly used for 3D graphics, data modeling, 2D plotting, image processing, and scientific visualization. It can be used with different types of algorithms and more advanced modeling data. It was created using the C++ class library along with Kitware, Python, Java, and Tcl/Tk.
Learn more about VTK
25. Zoho Analytics
For smaller projects, Zoho Analytics offers a free version for 2 users, 5 workspaces, and 10,000 rows. Any data source can be connected from the web to flat files and it will be synced automatically and scheduled. It has many visualizations, drag and drop reporting features, incredible dashboards, data interactions, and geo-visualization.
Learn more about Zoho Analytics
Of the 25 free project management software tools out there, we recommend trying out the solution that will help you best achieve your goals. However, it is important to remember that not all the best tools are free. Sometimes, you have to invest in order to get the best results.
Frequently Asked Questions about DataViz Tools:
What is the best free data visualization software?
Most people think Tableau Software offers an easy way for anyone to create beautiful visualizations using their own data but would be for non commercial use. It also allows you to share them with others easily. You can use Tableau Public or Tableau Server to publish your work online.
It allows users to create interactive dashboards with charts, graphs, maps, and tables. Users can also share their work online for others to use.
Still, use what works best for your needs and scope of project. You can find a powerful tool, templates, an array of charts that come with analytics tools to help you for free but check limits.
Does Excel have data visualization tools?
Yes! You can use Excel for creating charts, graphs, maps, and dashboards. You can also create interactive reports with embedded links so users can navigate through them easily.
Is Python a data visualization tool?
No, Python by itself is an open-source programming language used for creating programs that manipulate text and numbers. It is also used for developing web applications. It was originally designed for scientific computing but now also serves as a go-to scripting language.
Python is often used with libraries such as Matplotlib to create interactive visualization.
Is SQL a data visualization tool?
No, SQL (also known as Structured Query Language) is used for database management. It allows you to create complex queries on large amounts of data. A good example would be if you wanted to find out how many people are registered at an event or what their favorite color is.
Data visualizations are not part of its core functionality.