Top 10 Tools for Building Interactive Graphs and Diagrams

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In software development we need to know about complex data, algorithms and systems. Data visualization, in its one of the best ways to get this and turn the raw data into clear understandable visual formats. By making data more interactive and by letting people communicate with them intuitively through interactive graphs and diagrams, the data is easier for people to comprehend at scale and identify patterns and relationships within big datasets or in complex algorithms.

In this article, we will discuss the best data visualization tools — interactive graphs and diagrams which a developer can use while working on his projects. But no matter if you want to create visualizations for debugging your code or if you’re going to present data driven insights, the right tool can help.

Overview of Data Visualization Tools

There are so many tools to visualize data. Finding the right tool to do interactive graphs and diagrams, however, can be tricky though. What you want will determine the type of visualizations you need and how easy is to use the tool, but in the end, the right tool will vary based on factors such as ease of use or compatibility with programming languages.

Then, these tools can help you to design everything including the network graphs, the heat maps, and all of the interactive features that allow them to explore and filter the data points, zoom in and out are now available for the users. In the case of complex systems, a well design tool makes developers and teams work on charts more intuitively.

Today, we’ll focus on the best free data visualization tools, and everything from those tools that are free of charge to those that offer a free version or trial. For beginners, seasoned professionals on a budget or a smaller team these tools could be a great choice.

Top 10 Tools for Building Interactive Graphs and Diagrams

1. D3.js

In simple terms, D3.js is a JavaScript library for creating dynamically and interactively visualizing data in web browser. Its one of the most popular tool for building complex visualizations.

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• Features: D3.js offers potent attributes for mapping Data to a document object model (DOM) as well as data driven transformations. It’s great for making bars charts to complex network diagrams.
• Strengths: With D3.js, developers have unparalleled flexibility, and are given full control over how their visualizations should appear and behave.
• Use Case: It’s best used when you’re constructing a highly customizable, complex visualization that melds nicely into a web application.
• Compatibility: Works great with JavaScript and well integrated with web frameworks like React, Angular, and Vue.

2. Plotly

Plotly is a popular tool for creating charts and graphs, which are fully interactive. By using Tachyon, users can create impressive graphics, which range from simple line graphs to fascinating 3-D graphs.

• Features: Many visualization types can be created using Plotly, this includes heat plots, bar plots, scatter plots, etc. It also permits users to create widgets in those dashboards that can be changed by users.
• Strengths: When it comes to using it, Plotly has the best interface with multiple languages support as it is supported and can be used in Python, R and JavaScript.
• Use Case: Best suited for big data, data analytics and data visualization scenarios where the users need to engage people with data.
• Compatibility: Supports Python, R and JavaScript languages enabling it to work without conflicts in programming languages.
• Free Version: Still, Plotly provides a free version with few capabilities, which can suit a developer with few bucks to spend.

3. Chart.js

It is an open-source simple and efficient chart library written in JavaScript used in the creation of interactive charts.

• Features: Chart.js categorizes into simple categories including line chart, bar chart, and pie chart. It can easily be adopted as it is small and can be installed on the working interface.
• Strengths: Versatile, comfortable to use, not too heavy and ideal for small to medium sized tasks. Chart.js is also well-documented and there is also a good number of people who are interested in this library.
• Use Case: Suits for use in adding simple, embodied interactivity to websites and web applications.
• Compatibility: Specifically, works with JavaScript and can be used to complement most of the contemporary Web development frameworks.
• Free Version: It is completely free and open source.

4. Cytoscape.js

Cytoscape.js is a free to use JavaScript library for developing network graph visualizations. Again it is more useful for displaying features or relations withing the networks of data.

• Features: borrowing the meaning from the name, it enables the creation of an intuitive and animated network diagram conveniently applicable to graphs, social networks, and various other systems connected in one way or another.
• Strengths: Cytoscape.js is very customizable and opens the door for different layout options so that users can generating stunning network diagrams.
• Use Case: Work best in projects that can benefit from bringing out relation in the large data set like the connection of the people on social site or a scientific research connection.
• Compatibility: Interactive with JavaScript and can be embraced alongside a variety of web frameworks.
• Free Version: It is entirely open source and can be used without any charge.

5. Google Charts

Google Charts is graphical web-based tool that is quite effective when it comes to developing web application that requires graphs and charts.

• Features: Google Charts option available for charting again encompasses several types of charting: Line charting, bar charting and scatter chart. It also supports charting to HTML and adding interactivity in web page.
• Strengths: It is very easy to put into use and they offer more documentation compared to most. Google Charts is highly compatible with other Google tools, so if you are a user of Google tools, then you will find it preferable to work with it.
• Use Case: Most suitable for web based applications for fast interactive data presentation.
• Compatibility: Compatible with JavaScript and can seamlessly be incorporated into the multiple frameworks.
• Free Version: Completely free for use.

6. Vis.js

Vis.js is a powerful open source library allowing to build visually rich and interactive products such as graphs, networks and timelines.

• Features: The denotation of its name, Vis.js, implies dynamic and real-time connected graphics, such as the networks and hierarchal charts.
• Strengths: As it is characterised by features like zoom-in/out, drag-and-drop or other features like real-time update.
• Use Case: Ideal for projects which require network diagrams which are interactive or require updates at frequent intervals.
• Compatibility: Supports JavaScript and can be combined with frameworks such Vue, React or Angular.
• Free Version: Open source, although there is some possibility of making money missing some features.

7. Bokeh

Bokeh is a Python library that makes data graphics for present day web browsers. It’s most valuable for generating good charts and graphs and for creating useable and good looking dashboards.

• Features: It is used to design various type of visualizations right from simple line charts up to dynamic dashboards. It is suitable for both to fix and updating information in real time.
• Strengths: Bokeh works well with other Python-based data analysis tools and is perfect for creating Web-based interactive plots.
• Use Case: Recommended for data scientists and analysts depending on the type of script language they incorporate in their workflows especially Python.
• Compatibility: Owns a primary expertise in Python but can interface with web frameworks with JavaScript language.
• Free Version: Completely non-commercial and it is available in the open source domain.

8. Sigma.js

Sigma.js is a designed JavaScript library that can draw and navigate through large networks, consisting of nodes and edges.

• Features: They can apply a wide range of interactivity with easily configurable network graph zoom/pan capabilities.
• Strengths: Sigma.js is designed for versatility, especially for large and complex network graphs that require real time engagement.
• Use Case: Most suitable for projects that require network analysis, social media graphs or any other application involving нескольких elements interconnections.
• Compatibility: Compatible with JavaScript, and can be included into web applications.
• Free Version: Free and open-source.

9. RawGraphs

RawGraphs is an extensible and completely open data visualization toolkit, for creating easy to customize graphics with very little coding.

• Features: This tool is very friendly to use and is capable of producing defined heat maps, spots, and bar graphs among others.
• Strengths: RawGraphs is quite easy to use, the tool can be instantiated through the browser and it has a drag and drop system to create the visualization.
• Use Case: Good for developers who need to get visual data but do not aim at coding a powerful and multi-functional application.
• Compatibility: It can be interfaced directly on the web tool and, therefore, can be used on any platform in place.
• Free Version: Free and open-source.

10. FusionCharts

FusionCharts is a charting library that can be used by developers to add some nice looking and interactive chart to web application.

• Features: FusionCharts currently has released over 90 types of charts ranging from simple bar and pie charts to complex gauges and maps. It includes features such as drill down and tool tip.
• Strengths: It has a basic API and PowerBI provides many options for customization that enables developers to make advanced interactive visualizations.
• Use Case: Good for companies’ terminals and applications that require the use of dynamic charts displaying updated data.
• Compatibility: Compatible with JavaScript and can be used with Angular and React, for instance.
• Free Version: The free version of FusionCharts is available with lesser functionalities.

Data Visualization Tools and Techniques

That is why when working with data visualization tools one should understand one or another type of visualization. Such techniques are heat maps, flowcharts, network graphs and others. Each kind of visualization is applicable for certain kind of data and for the certain message that you want to convey.

• Heat Maps: Chart or picture in which values are represented by colour. Tables are perfect for displaying trends in big data sets.
• Flow Charts: Perfect for use in the presentation of processes, workflows or systems. Each visualization offers the possibility to click on a path and to go back or forward to see the steps.
• Network Graphs: Useful when one wishes to display interactions of elements in a network for instance social networks or transport networks.

Selecting the right tool for the right technique can make your data easy to comprehend, as well as aesthetically pleasing.

Conclusion

The tools to use in data visualization therefore depends on the project you have in mind. If you’re a developer interested in creating dynamic and engaging graphs and charts, then D3.js, Plotly and Google Charts are ideal. It is also important to note that the majority of the tools listed above have free or open source versions and would therefore make a convenient choice for developers who are operating on a tight budget.

If you match the tool to your project requirements and familiarize yourself with the most efficient ways of visualizing, you can provide a clear view of your data and make correct conclusion enhancing group decision making.