Core Plot vs Matplotlib

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

Core Plot is a Development solution with tags like plotting, charting, data-visualization, macos, ios, tvos.

It boasts features such as 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 pros including Fast and optimized for mobile, Lightweight and easy to integrate, Good documentation, Active development and support, Very customizable and extensible, Open source and free.

On the other hand, Matplotlib is a Photos & Graphics product tagged with plotting, graphs, charts, visualization, python.

Its standout features include 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 it shines with pros like 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.

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

Product Overview

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.

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.

Key Features Comparison

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

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

Pros & Cons Analysis

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

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)

Pricing Comparison

Core Plot

• Open Source

Matplotlib

• Open Source