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!

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.

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.

class pandas.DataFrame(data=None, index=None, columns=None, dtype=None, copy=None) [source] # Two-dimensional, size-mutable, potentially heterogeneous tabular data.

pandas provides various facilities for easily combining together Series and DataFrame objects with various kinds of set logic for the indexes and relational algebra functionality in the case of join / …

How do I read and write tabular data? How do I select a subset of a DataFrame? How do I create plots in pandas? How to create new columns derived from existing columns How to calculate summary …

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, with many …

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 cross-platform …

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.

Essential basic functionality # Here we discuss a lot of the essential functionality common to the pandas data structures. To begin, let’s create some example objects like we did in the 10 minutes to pandas …