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! Getting started

The user guide provides in-depth information on the key concepts of pandas with useful background information and explanation.

For users that are new to Python, the easiest way to install Python, pandas, and the packages that make up the PyData stack (SciPy, NumPy, Matplotlib, and more) is with Anaconda, a …

pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the …

For a quick overview of pandas functionality, see 10 Minutes to pandas. You can also reference the pandas cheat sheet for a succinct guide for manipulating data with pandas. The …

The User Guide covers all of pandas by topic area. Each of the subsections introduces a topic (such as “working with missing data”), and discusses how pandas approaches the problem, …

pandas cheat sheet Try pandas in your browser (experimental) You can try pandas in your browser with the following interactive shell without needing to install anything on your system.

The easiest way for the majority of users to install pandas is to install it as part of the Anaconda distribution, a cross platform distribution for data analysis and scientific computing. This is the …

Concatenate pandas objects along a particular axis. get_dummies (data[, prefix, prefix_sep, ...]) Convert categorical variable into dummy/indicator variables.

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