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D3.js

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D3.js vs Matplotlib: What are the differences?

Introduction

D3.js (Data-Driven Documents) and Matplotlib are both popular data visualization libraries, but they have key differences in terms of their features, syntax, and use cases.

  1. Syntax: D3.js is primarily a JavaScript library, while Matplotlib is a Python library. D3.js uses a declarative approach, where the visualization code is tightly integrated with HTML and CSS. On the other hand, Matplotlib has a procedural interface, where plots are created by calling functions and methods.

  2. Interactivity: D3.js is known for its powerful interactivity capabilities. It provides extensive support for creating interactive and dynamic visualizations, such as interactive charts, zooming, panning, and brushing. Matplotlib, on the other hand, focuses more on static visualizations and lacks the same level of built-in interactivity as D3.js.

  3. Data Binding: D3.js excels at data binding, allowing developers to easily connect data elements to visual elements. This enables efficient updates and transitions when the underlying data changes. Matplotlib, while capable of handling data, does not have the same level of flexibility and ease of data binding as D3.js.

  4. Rendering: D3.js renders visualizations directly in the browser using SVG (Scalable Vector Graphics) or HTML5 Canvas. This allows for high-quality and scalable plots that can be easily integrated into web applications. In contrast, Matplotlib primarily renders visualizations as static images or SVG files, which are not as flexible for integration in dynamic web environments.

  5. Community and Ecosystem: D3.js has a vibrant community and a rich ecosystem of plugins and extensions. It is widely used for creating interactive web-based visualizations and has extensive documentation and resources available. Matplotlib also has a large user base, but its ecosystem is more focused on static plotting in scientific and data analysis domains.

  6. Learning Curve: D3.js has a steeper learning curve compared to Matplotlib. Its extensive API and functional programming style can be challenging for beginners. Matplotlib, on the other hand, has a simpler and more intuitive interface, making it easier to get started with basic visualization tasks.

In Summary, D3.js and Matplotlib have different strengths and use cases. D3.js is suited for interactive web-based visualizations with dynamic data, while Matplotlib is more suitable for static visualizations and scientific plotting in Python.

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Pros of D3.js
Pros of Matplotlib
  • 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
  • 10
    The standard Swiss Army Knife of plotting

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Cons of D3.js
Cons of Matplotlib
  • 11
    Beginners cant understand at all
  • 6
    Complex syntax
  • 5
    Lots of code

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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 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.

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Blog Posts

Sep 8 2017 at 2:54PM

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What are some alternatives to D3.js and Matplotlib?
three.js
It is a cross-browser JavaScript library and Application Programming Interface used to create and display animated 3D computer graphics in a web browser.
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.
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.
Python
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
Tableau
Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
See all alternatives