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Chartist.js

21
47
+ 1
10
D3.js

1.8K
1.7K
+ 1
653
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CHARTIST.JS vs D3.js: What are the differences?

  1. Data Visualization Capabilities: CHARTIST.JS focuses on providing simple and responsive charts using SVG while D3.js is known for its flexibility and ability to create highly customized and complex visualizations using SVG, HTML, and CSS.
  2. Learning Curve: CHARTIST.JS has a lower learning curve compared to D3.js, making it more accessible for beginners and those looking to quickly create attractive charts without delving into deep JavaScript coding.
  3. Community Support: D3.js has a larger and more active community compared to CHARTIST.JS, leading to more resources, tutorials, plugins, and support available for users looking to extend and customize their visualizations.
  4. Browser Compatibility: CHARTIST.JS is designed to work best with modern browsers, while D3.js offers better compatibility with older browsers, allowing for a wider range of users to access the visualizations.
  5. Animation Capabilities: D3.js provides more advanced and dynamic animation capabilities, allowing for complex transitions and interactions, while CHARTIST.JS offers simpler and more straightforward animations for basic chart elements.
  6. Plugins and Extensions: D3.js has a vast collection of plugins and extensions available, offering users a wide range of additional functionalities and features to enhance their visualizations, whereas CHARTIST.JS has a limited number of plugins and extensions available.

In Summary, CHARTIST.JS focuses on simplicity and responsiveness, while D3.js is more powerful and customizable but comes with a steeper learning curve.

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Pros of Chartist.js
Pros of D3.js
  • 5
    Small size
  • 4
    SVG
  • 1
    Animations
  • 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 Chartist.js
Cons of D3.js
  • 2
    Weak documentation
  • 11
    Beginners cant understand at all
  • 6
    Complex syntax

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What is Chartist.js?

It is an open source Charting JavaScript library which provide a solution to the problems faced by charting libraries. It’s lightweight, simple and flexible to integrate . You can Create responsive, scalable and good looking charts with it.

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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What companies use D3.js?
See which teams inside your own company are using Chartist.js or D3.js.
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Blog Posts

Sep 8 2017 at 2:54PM

Eventbrite-0

JavaScriptNode.jsReact+7
6
9776
What are some alternatives to Chartist.js and D3.js?
Chart.js
Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.
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.
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.
C3.js
c3 is a D3-based reusable chart library that enables deeper integration of charts into web applications.
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.
See all alternatives