The Python Graph Gallery
👋 The Python Graph Gallery is a collection of hundreds of charts made with Python.
Graphs are dispatched in about 40 sections following the data-to-viz classification. There are also sections dedicated to more general topics like matplotlib or seaborn.
Each example is accompanied by its corresponding reproducible code along with comprehensive explanations. The gallery offers tutorials that cater to beginners to help kickstart their journey, as well as advanced examples that demonstrate the potency of Python in the realm of data visualization.
❤️ Love the project?
You can contribute on github, send me a feedback on twitter or subscribe to the newsletter to know when new examples are published! 🔥
The biggest list of python chart examples
Within our collection, we cover every chart type imaginable to ensure we fullfil your data visualization needs. To streamline the process of finding your required chart, we meticulously classified all the examples under their respective chart types.
For each chart type, we kick off with a foundational tutorial that introduces its basic structure and utility. After mastering the basics, users can delve into our step-by-step guides on the most elementary customizations, ensuring your chart not only presents data but does so with an individual touch that caters to your specific requirements.
General Knowledge
Colors
Interactivity
Animation
Cheat sheets
Caveats
3D
Statistics
Hunting the most beautiful Python charts
Explore our curated collection of the finest Python charts, handpicked for their superior design and accuracy. Go beyond the defaults with chart examples that are both visually stunning and instructive.
Accompanied by in-depth tutorials, this section will please seasoned professionals aspiring to elevate their craft. Featuring the finest charts on the web, we stay ahead of the curve, showcasing the latest tips, tricks, and advanced techniques in data visualization.
Python Graphing with State-of-the-Art Libraries
The python graph gallery relies on the latest and most powerful charting libraries.
Matplotlib
The foundation of Python visualization. Offers a wide array of customizable 2D plots and an extensive set of tools for creating intricate figures and charts.
Tutorial
Seaborn
Built atop Matplotlib, Seaborn elevates data visualization by providing a higher-level interface and stunning default themes.
Tutorial
Pandas
Beyond its powerful data manipulation capabilities, Pandas offers convenient plotting methods, enabling users to visualize data directly from DataFrame and Series objects.
Tutorial
Plotly
Delivering interactive and browser-based visualizations, Plotly allows users to craft visually captivating charts, bridging the gap between static graphs and web-based interactivity.
TutorialContact
👋 This document is a work by Yan Holtz. You can contribute on github, send me a feedback on twitter or subscribe to the newsletter to know when new examples are published! 🔥