some small regression fixes, bug fixes and performance improvements. We recommend that all users upgrade to this version. Highlights include: • Temporarily restore matplotlib datetime plotting functionality and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: • Integration with Apache Parquet, including a new top-level 20.x series and includes some small regression fixes and bug fixes. We recommend that all users upgrade to this version. What’s new in v0.20.3 • Bug Fixes – Conversion – Indexing – I/O – Plotting

20.x series and includes some small regression fixes and bug fixes. We recommend that all users upgrade to this version. What’s new in v0.20.3 • Bug Fixes – Conversion – Indexing – I/O – Plotting some small regression fixes, bug fixes and performance improvements. We recommend that all users upgrade to this version. What’s new in v0.20.2 • Enhancements 4 Chapter 1. What’s New pandas: powerful and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: • New .agg() API for Series/DataFrame similar to the grou

some small regression fixes, bug fixes and performance improvements. We recommend that all users upgrade to this version. What’s new in v0.20.2 • Enhancements • Performance Improvements • Bug Fixes and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: • New .agg() API for Series/DataFrame similar to the grou some small regression fixes, bug fixes and performance improvements. We recommend that all users upgrade to this version. Highlights include: • Compatibility with Python 3.6 • Added a Pandas Cheat Sheet

that was deprecated in previous releases (see below for an overview). It is recommended to first upgrade to pandas 0.25 and to ensure your code is working without warnings, before upgrading to pandas 1 which may appear when querying stores using an index. If you see a subset of results being returned, upgrade to PyTables >= 3.2. Stores created previously will need to be rewritten using the updated version For full details, see the commit logs at http://github.com/ pandas-dev/pandas. For install and upgrade instructions, see Installing statsmodels. 6.1 Version 1.0 6.2 Version 0.25 6.2.1 What’s new in

which may appear when querying stores using an index. If you see a subset of results being returned, upgrade to PyTables >= 3.2. Stores created previously will need to be rewritten using the updated version For full details, see the commit logs at http://github.com/ pandas-dev/pandas. For install and upgrade instructions, see Installation. 8.1 Version 0.25 8.2 Version 0.24 8.2.1 Whats new in 0.24.2 (March 23.x series and includes some small regression fixes and bug fixes. We recommend that all users upgrade to this version. Warning: Starting January 1, 2019, pandas feature releases will support Python

which may appear when querying stores using an index. If you see a subset of results being returned, upgrade to PyTables >= 3.2. Stores created previously will need to be rewritten using the updated version For full details, see the commit logs at http://github.com/ pandas-dev/pandas. For install and upgrade instructions, see Installation. 8.1 Version 0.25 8.1.1 What’s new in 0.25.1 (August 21, 2019) 23.x series and includes some small regression fixes and bug fixes. We recommend that all users upgrade to this version. Warning: Starting January 1, 2019, pandas feature releases will support Python

some small regression fixes, bug fixes and performance improvements. We recommend that all users upgrade to this version. What’s new in v0.19.1 • Performance Improvements • Bug Fixes Performance Improvements and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: • merge_asof() for asof-style time-series joining, see here with several new features, enhancements, and performance improvements. We recommend that all users upgrade to this version. Highlights include: • .groupby(...) has been enhanced to provide convenient syntax

which may appear when querying stores using an index. If you see a subset of results being returned, upgrade to PyTables >= 3.2. Stores created previously will need to be rewritten using the updated version For full details, see the commit logs at http://github.com/ pandas-dev/pandas. For install and upgrade instructions, see Installation. 5.1 Version 1.0 5.1.1 What’s new in 1.0.5 (June 17, 2020) These that was deprecated in previous releases (see below for an overview). It is recommended to first upgrade to pandas 0.25 and to ensure your code is working without warnings, before upgrading to pandas 1

which may appear when querying stores using an index. If you see a subset of results being returned, upgrade to PyTables >= 3.2. Stores created previously will need to be rewritten using the updated version For full details, see the commit logs at http://github.com/ pandas-dev/pandas. For install and upgrade instructions, see Installation. 5.1 Version 1.0 5.1.1 What’s new in 1.0.4 (May 28, 2020) These that was deprecated in previous releases (see below for an overview). It is recommended to first upgrade to pandas 0.25 and to ensure your code is working without warnings, before upgrading to pandas 1

which may appear when querying stores using an index. If you see a subset of results being returned, upgrade to PyTables >= 3.2. Stores created previously will need to be rewritten using the updated version of changes to pandas between each release. For full details, see the commit logs. For install and upgrade instructions, see Installation. 5.1 Version 1.1 5.1.1 What’s new in 1.1.0 (July 28, 2020) These that was deprecated in previous releases (see below for an overview). It is recommended to first upgrade to pandas 0.25 and to ensure your code is working without warnings, before upgrading to pandas 1