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Matplotlib vs Plotly: What are the differences?

Introduction

Matplotlib and Plotly are both popular libraries used for data visualization in Python. While they serve the same purpose, there are several key differences between the two. In this article, we will explore these differences and compare the features and functionalities of Matplotlib and Plotly.

  1. Plotting Style and Interactivity: Matplotlib is a static library that produces basic visualizations with a simple syntax. It uses a simple procedural approach to create static images of plots. On the other hand, Plotly is an interactive library that supports highly interactive and dynamic visualizations with a more complex syntax. It allows users to create animated and interactive plots that can be embedded in websites and shared online.

  2. Backend and Rendering: Matplotlib uses a backend system that determines how the plots are rendered. It supports various backends including the default "agg" backend for non-interactive rendering and "TkAgg" backend for interactive rendering in GUI environments. Plotly, on the other hand, uses its own WebGL-based graphics engine that allows for smoother and faster rendering of interactive plots in web browsers.

  3. Ease of Use: Matplotlib is known for its simplicity and ease of use. It provides a simple and intuitive API for creating basic plots quickly. However, creating complex and interactive plots may require more coding and customization. On the other hand, Plotly provides a higher-level API that makes it easier to create complex plots with less code. It also offers a wide range of pre-built charts and templates that can be customized with ease.

  4. Online Collaboration and Sharing: Plotly has a strong focus on online collaboration and sharing. It provides an online platform called plotly.py where users can create, edit, and share their plots with others. This platform also supports version control, collaboration, and sharing of plots through social media or embedded code. Matplotlib, on the other hand, lacks these online collaboration features and is mainly used for offline plotting and visualization.

  5. Support for Web Technologies: Plotly is built on web technologies such as HTML, CSS, and JavaScript, which makes it more suited for web-based applications and dashboards. It supports interactive features such as zooming, panning, and hover tooltips, which are not readily available in Matplotlib. Matplotlib, on the other hand, is better suited for generating static images for publications and offline analysis.

  6. Integration with Jupyter Notebooks: Both Matplotlib and Plotly can be used with Jupyter Notebooks, but they provide different integration options. Matplotlib can render plots directly in Jupyter Notebooks using the %matplotlib inline magic command. Plotly, on the other hand, provides a JupyterLab extension called "plotly-extension" that allows users to create and interact with Plotly plots within JupyterLab.

In summary, Matplotlib is a simple and flexible library for creating basic visualizations, while Plotly is a more powerful and interactive library that is well-suited for creating complex and dynamic plots for web-based applications and collaboration.

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Pros of Matplotlib
Pros of Plotly.js
  • 10
    The standard Swiss Army Knife of plotting
  • 16
    Bindings to popular languages like Python, Node, R, etc
  • 10
    Integrated zoom and filter-out tools in charts and maps
  • 9
    Great support for complex and multiple axes
  • 8
    Powerful out-of-the-box featureset
  • 6
    Beautiful visualizations
  • 4
    Active user base
  • 4
    Impressive support for webgl 3D charts
  • 3
    Charts are easy to share with a cloud account
  • 3
    Webgl chart types are extremely performant
  • 2
    Interactive charts
  • 2
    Easy to use online editor for creating plotly.js charts
  • 2
    Publication quality image export

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Cons of Matplotlib
Cons of Plotly.js
  • 5
    Lots of code
  • 18
    Terrible document

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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.

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 are some alternatives to Matplotlib and Plotly.js?
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.
MATLAB
Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.
Bokeh
Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.
R Language
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
ggplot2
It is a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers.
See all alternatives