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C3.js

264
161
+ 1
4
NVD3

80
30
+ 1
0
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Pros of C3.js
Pros of NVD3
  • 2
    Easy to use
  • 2
    Reusable charts
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    Cons of C3.js
    Cons of NVD3
    • 1
      Dependent on D3.js which is not lightweight
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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 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.

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      What companies use C3.js?
      What companies use NVD3?
      See which teams inside your own company are using C3.js or NVD3.
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      What tools integrate with C3.js?
      What tools integrate with NVD3?

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      What are some alternatives to C3.js and NVD3?
      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.
      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.
      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