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C3.js

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C3.js vs D3.js: What are the differences?

Introduction

C3.js and D3.js are both popular JavaScript libraries used for data visualization. While they share some similarities, there are key differences between the two.

  1. Programming Model: C3.js is built on top of D3.js and provides a higher-level programming model. It abstracts away many of the complexities of D3.js, making it easier to create charts and graphs. C3.js provides a simple and intuitive API, allowing developers to quickly generate visualizations with less code compared to D3.js.

  2. Chart Types: C3.js focuses on providing predefined chart types and customization options. It offers a wide range of chart types such as line charts, bar charts, pie charts, and scatter plots. These chart types come with default configurations and styling options, making it convenient for developers to create common types of visualizations. On the other hand, D3.js provides a lower-level interface and allows for more flexibility in creating custom chart types and visualizations from scratch.

  3. Data Binding: D3.js emphasizes data binding and provides powerful data manipulation capabilities. It allows developers to bind data to different elements of a chart, update the data dynamically, and animate transitions. D3.js provides a data-driven approach, where the visual representation of data is directly tied to the underlying data structure. C3.js, on the other hand, simplifies data binding by handling it internally. Developers can pass data to C3.js in a simple format, and it takes care of the rest, making it easier to create visualizations quickly.

  4. Documentation and Community: D3.js has a large and active community with extensive documentation, tutorials, and examples. It is a more mature library with a wide range of resources available. C3.js, although built on D3.js, has a smaller community and fewer resources. The documentation for C3.js is not as comprehensive as D3.js. This can be a factor to consider when choosing between the two libraries, especially for developers looking for extensive support and resources.

  5. Customization and Styling: D3.js provides unparalleled customization and styling options. It allows developers to have fine-grained control over every aspect of a chart, including the design, layout, and behavior. The customizability of D3.js makes it suitable for creating unique and highly customized visualizations. While C3.js also allows some level of customization, it is more limited compared to D3.js. C3.js focuses on providing a streamlined experience by offering predefined styling options and configurations.

  6. Learning Curve: D3.js has a steeper learning curve compared to C3.js. It requires a deeper understanding of JavaScript, HTML, CSS, and SVG. Developing complex visualizations with D3.js often requires a significant investment of time and effort. On the other hand, C3.js abstracts away many of the low-level details, making it easier to get started and create charts quickly. C3.js is more suitable for developers who want to create visualizations without diving into the intricacies of D3.js.

In Summary, C3.js provides a higher-level programming model with predefined chart types and simplified data binding, making it more accessible and convenient for creating visualizations. D3.js, on the other hand, offers more flexibility, customization options, and powerful data manipulation capabilities for developers who require advanced and highly customized visualizations.

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Pros of C3.js
Pros of D3.js
  • 2
    Easy to use
  • 2
    Reusable charts
  • 195
    Beautiful visualizations
  • 103
    Svg
  • 92
    Data-driven
  • 81
    Large set of examples
  • 61
    Data-driven documents
  • 24
    Visualization components
  • 20
    Transitions
  • 18
    Dynamic properties
  • 16
    Plugins
  • 11
    Transformation
  • 7
    Makes data interactive
  • 4
    Open Source
  • 4
    Enter and Exit
  • 4
    Components
  • 3
    Exhaustive
  • 3
    Backed by the new york times
  • 2
    Easy and beautiful
  • 1
    Highly customizable
  • 1
    Awesome Community Support
  • 1
    Simple elegance
  • 1
    Templates, force template
  • 1
    Angular 4

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Cons of C3.js
Cons of D3.js
  • 1
    Dependent on D3.js which is not lightweight
  • 11
    Beginners cant understand at all
  • 6
    Complex syntax

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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.

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See which teams inside your own company are using C3.js or D3.js.
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What tools integrate with D3.js?

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Blog Posts

Sep 8 2017 at 2:54PM

Eventbrite-0

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What are some alternatives to C3.js and D3.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.
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.
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.
See all alternatives