pandas - Python Data Analysis Library
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. It offers data manipulation capabilities that are essential for data science, including data alignment, handling of missing data, reshaping, merging, and grouping of datasets. Pandas is widely used in academic and commercial sectors, including finance, neuroscience, economics, statistics, advertising, web analytics, and more.
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Key Features of the Site
DataFrame
A two-dimensional, size-mutable, and potentially heterogeneous tabular data structure with labeled axes (rows and columns).
Series
A one-dimensional labeled array capable of holding any data type.
Data Alignment
Intrinsic data alignment and integrated handling of missing data.
Reshaping and Pivoting
Tools for reshaping and pivoting datasets.
Time Series
Functionality for working with time series data, including date range generation and frequency conversion.
GroupBy
Allows for aggregation and transformations on subsets of data.
Merging and Joining
Facilities for merging and joining datasets.
Input/Output Tools
Tools for reading and writing data between in-memory data structures and different file formats.
Performance
Highly optimized for performance, with critical code paths written in Cython or C.
Additional information
License
BSD
Repository
https://github.com/pandas-dev/pandas
Documentation
Extensive documentation available at https://pandas.pydata.org/docs/
Community
Active community support through mailing lists, Stack Overflow, and GitHub issues.
Contributing
Contributions are welcome. Guidelines are provided in the repository.
Version
The latest stable version is 1.3.0 as of the last update.
HTTP headers
Security headers report is a very important part of user data protection. Learn more about http headers for pandas.pydata.org