Pandas
Efficiently manipulate and process structured data using Pandas' powerful library and community support.
Pandas is a robust library under NumFOCUS for handling structured data, providing data structures and functions for efficient manipulation, especially for tabular data. It offers features like subsetting, merging, reshaping, multi-level indexing, and reading/writing files in various formats. Development began at AQR Capital Management in 2008, and users seek help on StackOverflow and discuss generally on the pydata mailing list.
About Pandas
Pandas is a powerful data manipulation library developed under the NumFOCUS umbrella. It offers various data structures and functions to handle structured data, particularly tabular data, efficiently. The library provides features such as subsetting using boolean indexing, merging and joining datasets, reshaping data through pivot tables, multi-level indexing, reading and writing files in various formats like CSV, Excel, SQL databases, and HDF5. Its roots date back to 2008 when the development began at AQR Capital Management, a quantitative hedge fund. For assistance with usage-related queries, the community relies on StackOverflow, whereas general discussions take place on the pydata mailing list.