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C3.js vs D3.js vs Plotly: What are the differences?
C3.js, D3.js, and Plotly are popular JavaScript libraries used for data visualization on websites. Below are the key differences between these libraries:
1. **Learning Curve**: D3.js is considered to have a steep learning curve due to its low-level API that requires deep understanding of SVG, CSS, and JavaScript. C3.js, on the other hand, provides a higher-level API that simplifies the process of creating charts, making it easier for beginners. Plotly focuses on offering an intuitive interface and comprehensive documentation, making it user-friendly for users of all levels.
2. **Customization**: D3.js allows deep customization of every aspect of a chart, giving developers complete control over the visualizations. C3.js offers a simpler interface with predefined chart types and styles, limiting customization to some extent. Plotly provides a balance between customization and ease of use by offering various customization options through its interface.
3. **Interactivity**: D3.js provides extensive support for adding interactive elements to charts, allowing users to interact with data points and visuals in real-time. C3.js includes basic interactive features by default, such as tooltips and zooming, making it suitable for simple interactions. Plotly shines in interactivity by offering a wide range of interactive features and widgets for enhancing user engagement and data exploration.
4. **Community and Support**: D3.js has a large and active community that contributes to tutorials, examples, and plugins, providing comprehensive support for developers. C3.js has a growing community but may have fewer resources compared to D3.js. Plotly, being a commercial product, offers dedicated customer support and documentation, making it a reliable choice for businesses and professionals.
5. **Rendering Performance**: D3.js excels in rendering performance, as it directly manipulates the DOM for efficient updates and transitions, suitable for handling large datasets. C3.js abstracts the rendering process, which may have overhead compared to D3.js when dealing with complex visualizations. Plotly's rendering performance is optimized for web and mobile platforms, ensuring smooth user experience across devices.
6. **Integration and Compatibility**: D3.js can be seamlessly integrated with other JavaScript frameworks and libraries due to its flexibility, making it a preferred choice for developers working on complex web applications. C3.js is built on top of D3.js and provides easier integration with existing web projects that have less customization requirements. Plotly offers APIs for integrating its visualizations with various platforms, making it versatile for different development environments.
In Summary, the key differences between C3.js, D3.js, and Plotly lie in their learning curve, customization options, interactivity features, community support, rendering performance, and integration capabilities.
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Learn MorePros of C3.js
Pros of D3.js
Pros of Plotly.js
Pros of C3.js
- Easy to use2
- Reusable charts2
Pros of D3.js
- Beautiful visualizations195
- Svg103
- Data-driven92
- Large set of examples81
- Data-driven documents61
- Visualization components24
- Transitions20
- Dynamic properties18
- Plugins16
- Transformation11
- Makes data interactive7
- Open Source4
- Enter and Exit4
- Components4
- Exhaustive3
- Backed by the new york times3
- Easy and beautiful2
- Highly customizable1
- Awesome Community Support1
- Simple elegance1
- Templates, force template1
- Angular 41
Pros of Plotly.js
- Bindings to popular languages like Python, Node, R, etc16
- Integrated zoom and filter-out tools in charts and maps10
- Great support for complex and multiple axes9
- Powerful out-of-the-box featureset8
- Beautiful visualizations6
- Active user base4
- Impressive support for webgl 3D charts4
- Charts are easy to share with a cloud account3
- Webgl chart types are extremely performant3
- Interactive charts2
- Easy to use online editor for creating plotly.js charts2
- Publication quality image export2
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Cons of C3.js
Cons of D3.js
Cons of Plotly.js
Cons of C3.js
- Dependent on D3.js which is not lightweight1
Cons of D3.js
- Beginners cant understand at all11
- Complex syntax6
Cons of Plotly.js
- Terrible document17
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- No public GitHub repository available -
What is C3.js?
c3 is a D3-based reusable chart library that enables deeper integration of charts into web applications.
What is D3.js?
It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.
What is Plotly.js?
It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R).
It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.
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What companies use C3.js?
What companies use D3.js?
What companies use Plotly.js?
What companies use C3.js?
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What tools integrate with C3.js?
What tools integrate with D3.js?
What tools integrate with Plotly.js?
What tools integrate with C3.js?
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What are some alternatives to C3.js, D3.js, and Plotly.js?
Highcharts
Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.
NVD3
This project is an attempt to build re-usable charts and chart components for d3.js without taking away the power that d3.js gives you. This is a very young collection of components, with the goal of keeping these components very customizable, staying away from your standard cookie cutter solutions.
Chart.js
Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.
Matplotlib
It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.
amCharts
amCharts is an advanced charting library that will suit any data visualization need. Our charting solution include Column, Bar, Line, Area, Step, Step without risers, Smoothed line, Candlestick, OHLC, Pie/Donut, Radar/ Polar, XY/Scatter/Bubble, Bullet, Funnel/Pyramid charts as well as Gauges.