GraphingLib 1.5.0 Documentation
A Python library for creating publication-quality figures with ease.
Getting started
If you are new to GraphingLib, check out this section first to learn how to install and import GraphingLib.
Handbook
Once GraphingLib is installed, visit this section to learn how to use its different features.
Reference
If you are looking for more details on objects and their methods, visit this section.
GraphingLib: Making Data Visualization Easy#
GraphingLib is an open-source data visualization library in Python, designed to make plotting and data analysis both intuitive and efficient. Built on the robust foundations of Matplotlib, GraphingLib enhances readability, conciseness, and user-friendliness in the creation of figures.
Why Choose GraphingLib?#
Object-Oriented Design
GraphingLib simplifies Matplotlib’s complex API by introducing an object-oriented approach. Each element on the graph is an object with properties you can set and modify at any time, ensuring clean, intuitive code.
Integrated Data Analysis
GraphingLib goes beyond basic plotting. Perform curve fits, differentiation, integration, intersections, and other standard operations directly on Curve and Scatter objects. Calculate statistical properties of histograms. Use set operations on polygons. All these features are built into the library using the powerful capabilities of NumPy, SciPy, and Shapely.
User Defined Figure Styles
GraphingLib allows you to apply prepackaged or custom styles effortlessly. Our GUI Style Editor lets you create, modify, and save styles, which can then be applied with a simple keyword. You can even set your own style as the default for all your figures. With GraphingLib, you can customize your plots quickly while retaining full control over their appearance.