pandas pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. Install pandas now!

Tutorials You can learn more about pandas in the tutorials, and more about JupyterLab in the JupyterLab documentation. Books The book we recommend to learn pandas is Python for Data …

pandas aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open …

pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

STUMPY is a powerful and scalable Python library for modern time series analysis. At its core, STUMPY efficiently computes something called a matrix profile, which can be used for a wide variety of time …

Each of the subsections introduces a topic (such as “working with missing data”), and discusses how pandas approaches the problem, with many examples throughout.

WASM powered Jupyter running in the browser.Try pandas in your browser (experimental) Try our experimental JupyterLite live shell with pandas, powered by Pyodide. Please note it can take a while …

Especially if you have pandas code in production or maintain a library with pandas as a dependency, it is strongly recommended to run your test suites with the release candidate, and report any issue to our …

Team Contributors pandas is made with love by more than 2,000 volunteer contributors. If you want to support pandas development, you can find information in the donations page. Active maintainers

PDEP-14: Dedicated string data type for pandas 3.0 PDEP-17: Backwards compatibility and deprecation policy Implemented PDEP-4: Consistent datetime parsing PDEP-6: Ban upcasting in setitem-like …