powerful Python data analysis toolkit, Release 1.0.0 Date: Jan 29, 2020 Version: 1.0.0 Download documentation: PDF Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas arrays and the data set is larger (1 million rows or greater). For more details, see rolling apply documentation (GH28987, GH30936) 3 pandas: powerful Python data analysis toolkit, Release 1.0.0 1.2.2 Defining during the rolling aggregation. For more details and example usage, see the custom window rolling documentation 1.2.3 Converting to Markdown We’ve added to_markdown() for creating a markdown table (GH11052)

. . . . . . . . . . . . . . . 1085 29 Contributing to pandas 1125 29.1 Contributing to the documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1125 30 Release Notes statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure The two primary data structures of pandas, Series (1-dimensional) and DataFrame (2-dimensional) Python. • pandas has been used extensively in production in financial applications. Note: This documentation assumes general familiarity with NumPy. If you haven’t used NumPy much or at all, do invest some

. . . 2698 4.3 Contributing to the documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2701 4.3.1 About the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2719 4.3.3 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2719 4.3.4 Previewing changes . . . toolkit, Release 1.3.4 Date: Oct 17, 2021 Version: 1.3.4 Download documentation: PDF Version | Zipped HTML Previous versions: Documentation of previous pandas versions is available at pandas.pydata.org.

. . . 2698 4.3 Contributing to the documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2701 4.3.1 About the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2719 4.3.3 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2719 4.3.4 Previewing changes . . . powerful Python data analysis toolkit, Release 1.3.3 Date: Sep 12, 2021 Version: 1.3.3 Download documentation: PDF Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2421 4.1.4 Contributing to the documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2426 4.1.5 Contributing to the operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2481 ix 4.8.7 Documentation improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2481 4.8.8 Performance powerful Python data analysis toolkit, Release 1.1.1 Date: Aug 20, 2020 Version: 1.1.1 Download documentation: PDF Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2421 4.1.4 Contributing to the documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2426 4.1.5 Contributing to the operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2481 ix 4.8.7 Documentation improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2481 4.8.8 Performance powerful Python data analysis toolkit, Release 1.1.0 Date: Jul 28, 2020 Version: 1.1.0 Download documentation: PDF Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas

. . . 2620 4.3 Contributing to the documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2623 4.3.1 About the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2640 4.3.3 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2640 4.3.4 Previewing changes . . . powerful Python data analysis toolkit, Release 1.3.2 Date: Aug 15, 2021 Version: 1.3.2 Download documentation: PDF Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas

. . . . . . . . . . . . . . . 1195 29 Contributing to pandas 1251 29.1 Contributing to the documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1251 30 Release Notes statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure The two primary data structures of pandas, Series (1-dimensional) and DataFrame (2-dimensional) Python. • pandas has been used extensively in production in financial applications. Note: This documentation assumes general familiarity with NumPy. If you haven’t used NumPy much or at all, do invest some

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2329 4.1.4 Contributing to the documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2333 4.1.5 Contributing to the Numba-accelerated operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2386 4.8.7 Documentation improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2387 4.8.8 Package powerful Python data analysis toolkit, Release 1.0.5 Date: Jun 17, 2020 Version: 1.0.5 Download documentation: PDF Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2325 4.1.4 Contributing to the documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2329 4.1.5 Contributing to the Numba-accelerated operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2382 4.8.7 Documentation improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2383 4.8.8 Package powerful Python data analysis toolkit, Release 1.0.4 Date: May 28, 2020 Version: 1.0.4 Download documentation: PDF Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas