See the full installation instructions for minimum supported versions of required, recommended and optional dependencies. pytz - Brings the Olson tz database into Python which allows accurate and cross platform timezone calculations.python-dateutil - Provides powerful extensions to the standard datetime module.NumPy - Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arrays.The source code is currently hosted on GitHub at:īinary installers for the latest released version are available at the Python Generation and frequency conversion, moving window statistics, Time series-specific functionality: date range.(CSV and delimited), Excel files, databases,Īnd saving/loading data from the ultrafast HDF5 format Robust IO tools for loading data from flat files.Hierarchical labeling of axes (possible to have multiple.Split-apply-combine operations on data sets, for both aggregatingĭifferently-indexed data in other Python and NumPy data structures Powerful, flexible group by functionality to perform.Ignore the labels and let Series, DataFrame, etc. Automatic and explicit data alignment: objects canīe explicitly aligned to a set of labels, or the user can simply.
The broader goal of becoming the most powerful and flexible open source dataĪnalysis / manipulation tool available in any language. It aims to be the fundamental high-level building block forĭoing practical, real world data analysis in Python. Structures designed to make working with "relational" or "labeled" data bothĮasy and intuitive.
Pandas is a Python package that provides fast, flexible, and expressive data Pandas: powerful Python data analysis toolkit
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