Matplotlib vs Pygal

Struggling to choose between Matplotlib and Pygal? Both products offer unique advantages, making it a tough decision.

Matplotlib is a Photos & Graphics solution with tags like plotting, graphs, charts, visualization, python.

It boasts features such as 2D plotting, Publication quality output, Support for many plot types (line, bar, scatter, histogram etc), Extensive customization options, IPython/Jupyter notebook integration, Animations and interactivity, LaTeX support for mathematical typesetting and pros including Mature and feature-rich, Large user community and extensive documentation, Highly customizable, Integrates well with NumPy, Pandas and SciPy, Output can be saved to many file formats.

On the other hand, Pygal is a Development product tagged with charting, data-visualization, svg, python.

Its standout features include Generates SVG charts from data, Supports various chart types like bar, pie, line, etc, Customizable styles and themes, Integration with major Python web frameworks, and it shines with pros like Lightweight and easy to use, Produces good looking SVG charts, Lots of customization options, Good documentation.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Matplotlib

Matplotlib

Matplotlib is a comprehensive 2D plotting library for Python that allows users to create a wide variety of publication-quality graphs, charts, and visualizations. It integrates well with NumPy and Pandas data structures.

Categories:
Photos & Graphics Data Visualization
plotting graphs charts visualization python

Matplotlib Features

  1. 2D plotting
  2. Publication quality output
  3. Support for many plot types (line, bar, scatter, histogram etc)
  4. Extensive customization options
  5. IPython/Jupyter notebook integration
  6. Animations and interactivity
  7. LaTeX support for mathematical typesetting

Pricing

  • Open Source

Pros

Mature and feature-rich

Large user community and extensive documentation

Highly customizable

Integrates well with NumPy, Pandas and SciPy

Output can be saved to many file formats

Cons

Steep learning curve

Plotting code can be verbose

3D plotting support is limited

Cannot do web visualization (unlike Bokeh or Plotly)

Pygal

Pygal

Pygal is a Python charting library that allows you to generate SVG charts from data. Some key features include support for various chart types like bar charts, pie charts, line charts etc., customizable styles and themes, and integration with major Python web frameworks.

Categories:
Development Data Visualization
charting data-visualization svg python

Pygal Features

  1. Generates SVG charts from data
  2. Supports various chart types like bar, pie, line, etc
  3. Customizable styles and themes
  4. Integration with major Python web frameworks

Pricing

  • Open Source

Pros

Lightweight and easy to use

Produces good looking SVG charts

Lots of customization options

Good documentation

Cons

Limited chart types compared to some libraries

Not optimized for real-time data

Small user community