Package: python-pandas-doc (1.1.5+dfsg-2)

data structures for "relational" or "labeled" data - documentation

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 fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data:

 - Tabular data with heterogeneously-typed columns, as in an SQL
   table or Excel spreadsheet
 - Ordered and unordered (not necessarily fixed-frequency) time
   series data.
 - Arbitrary matrix data (homogeneously typed or heterogeneous) with
   row and column labels
 - Any other form of observational / statistical data sets. The data
   actually need not be labeled at all to be placed into a pandas
   data structure

This package contains the documentation.

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