Matplotlib vs Core Plot

Struggling to choose between Matplotlib and Core Plot? 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, Core Plot is a Development product tagged with plotting, charting, data-visualization, macos, ios, tvos.

Its standout features include High performance 2D plotting, Support for bar, line, scatter, pie, area and other plot types, Date plotting with customizable axes, Legend support, Customizable styles and themes, Zooming, panning, and scrolling, Export plots as images, Bind plots to Core Data and load data asynchronously, Mac, iOS, tvOS support, and it shines with pros like Fast and optimized for mobile, Lightweight and easy to integrate, Good documentation, Active development and support, Very customizable and extensible, Open source and free.

Feature	Matplotlib	Core Plot
Overall Score	N/A	N/A
Primary Category	Photos & Graphics	Development

Product Overview

Matplotlib

Description: 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.

Core Plot

Description: Core Plot is an open-source 2D plotting framework for macOS, iOS, and tvOS. It provides high-performance plotting, numerical analysis, and data visualization functionality to developers writing native Mac, iPhone, iPad, and Apple TV apps.

Key Features Comparison

Matplotlib Features

• 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

Core Plot Features

• High performance 2D plotting
• Support for bar, line, scatter, pie, area and other plot types
• Date plotting with customizable axes
• Legend support
• Customizable styles and themes
• Zooming, panning, and scrolling
• Export plots as images
• Bind plots to Core Data and load data asynchronously
• Mac, iOS, tvOS support

Pros & Cons Analysis

Matplotlib

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)

Core Plot

Pros

• Fast and optimized for mobile
• Lightweight and easy to integrate
• Good documentation
• Active development and support
• Very customizable and extensible
• Open source and free

Cons

• Limited built-in support for 3D plotting
• Steep learning curve
• Requires knowledge of Core Animation and Quartz
• Lacks some advanced statistical/analytics features

Pricing Comparison

Matplotlib

• Open Source

Core Plot

• Open Source