python(x,y) vs Core Plot

Struggling to choose between python(x,y) and Core Plot? Both products offer unique advantages, making it a tough decision.

python(x,y) is a Development solution with tags like plotting, data-visualization, charts, graphs.

It boasts features such as 2D and 3D plotting, Statistical graphs, Image processing and display, GUI widgets for user interfaces, Support for various file formats and pros including Open source and free to use, Large collection of plotting functions, Highly customizable plots, Interactively explore and visualize data, Integrates well with NumPy and SciPy.

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	python(x,y)	Core Plot
Overall Score	N/A	N/A
Primary Category	Development	Development

Product Overview

python(x,y)

Description: python(x,y) is an open-source mathematical plotting and data visualization library for the Python programming language. It provides a simple interface for creating 2D plots, histograms, power spectra, bar charts, errorcharts, contour plots, etc.

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

python(x,y) Features

• 2D and 3D plotting
• Statistical graphs
• Image processing and display
• GUI widgets for user interfaces
• Support for various file formats

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

python(x,y)

Pros

• Open source and free to use
• Large collection of plotting functions
• Highly customizable plots
• Interactively explore and visualize data
• Integrates well with NumPy and SciPy

Cons

• Steep learning curve
• Documentation can be lacking
• 3D plotting is limited
• Not ideal for web application backends

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

python(x,y)

• Open Source
• Free

Core Plot

• Open Source