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!

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 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 …

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 …

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 / …

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

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 …

Oct 9, 2011 · Starting with the upcoming pandas 3.0 release, a dedicated string data type will be enabled by default (backed by PyArrow under the hood, if installed, otherwise falling back to NumPy).