v0.20.1 Final

This is a minor release from 0.20.0 and includes a single change for backwards-compatibility with downstream projects using pandas' utils routines. See here.

See the Whatsnew file for more information. Please report any issues here.

The release can be installed with conda from the conda-forge channel (builds for osx-64, linux-64 and win-64 for Python 2.7, Python 3.5, and Python 3.6 are all available):

conda install -c conda-forge pandas

Or via PyPI:

pip install --upgrade pip setuptools
pip install --pre --upgrade --upgrade-strategy=only-if-needed pandas

v0.20.0 Final

This is a major release from 0.19.2 and includes a number of API changes, deprecations, new features,
enhancements, 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 groupby-rolling-resample API's, see here
• Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here
• The .ix indexer has been deprecated, see here
• Panel has been deprecated, see here
• Addition of an IntervalIndex and Interval scalar type, see here
• Improved user API when accessing levels in .groupby(), see here
• Improved support for UInt64 dtypes, see here
• A new orient for JSON serialization, orient='table', that uses the Table Schema spec, see here
• Experimental support for exporting DataFrame.style formats to Excel, see here
• Window Binary Corr/Cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here
• Support for S3 handling now uses s3fs, see here
• Google BigQuery support now uses the pandas-gbq library, see here
• Switched the test framework to use pytest

See the Whatsnew file for more information.

v0.20.0rc2

RELEASE CANDIDATE 2

This is a major release from 0.19.2 and includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug fixes.

Please try this RC and report any issues on the pandas issue tracker. We will be releasing officially a day or two.

Highlights include:

• new .agg() API for Series/DataFrame similar to the groupby-rolling-resample API's, see here
• Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here
• The .ix indexer has been deprecated, see here
• Panel has been deprecated, see here
• Addition of an IntervalIndex and Interval scalar type, see here
• Improved user API when accessing levels in .groupby(), see here
• Improved support for UInt64 dtypes, see here
• A new orient for JSON serialization, orient='table', that uses the Table Schema spec, see here
• Experimental support for exporting DataFrame.style formats to Excel, see here
• Window Binary Corr/Cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here
• Support for S3 handling now uses s3fs, see here
• Google BigQuery support now uses the pandas-gbq library, see here
• Switched the test framework to use pytest

See the Whatsnew file for more information. Please report any issues here.

The release candidate can be installed with conda from our development channel (builds for osx-64, linux-64 and win-64 for Python 2.7, Python 3.5, and Python 3.6 are all available):

conda install -c pandas pandas=0.20.0rc2

Or via PyPI

pip install --upgrade pip setuptools
pip install --pre --upgrade --upgrade-strategy=only-if-needed pandas

v0.20.0rc1

RELEASE CANDIDATE 1

This is a major release from 0.19.2 and includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug fixes.

Please try this RC and report any issues on the pandas issue tracker. We will be releasing officially in 1-2 weeks or so.

Highlights include:

• new .agg() API for Series/DataFrame similar to the groupby-rolling-resample API's, see here
• Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here
• The .ix indexer has been deprecated, see here
• Panel has been deprecated, see here
• Addition of an IntervalIndex and Interval scalar type, see here
• Improved user API when accessing levels in .groupby(), see here
• Improved support for UInt64 dtypes, see here
• A new orient for JSON serialization, orient='table', that uses the Table Schema spec, see here
• Experimental support for exporting DataFrame.style formats to Excel, see here
• Window Binary Corr/Cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here
• Support for S3 handling now uses s3fs, see here
• Google BigQuery support now uses the pandas-gbq library, see here
• Switched the test framework to use pytest

See the Whatsnew file for more information. Please report any issues here.

The release candidate can be installed with conda from our development channel (builds for osx-64, linux-64 and win-64 for Python 2.7, Python 3.5, and Python 3.6 are all available):

conda install -c pandas pandas=0.20.0rc1

Or via PyPI

pip install --upgrade pip setuptools
pip install --pre --upgrade --upgrade-strategy=only-if-needed pandas

v0.19.2 Final

This is a minor bug-fix release in the 0.19.x series and includes some small regression fixes, bug fixes and performance improvements.

Highlights include:

• Compatibility with Python 3.6
• Added a Pandas Cheat Sheet

See the v0.19.2 Whatsnew page for an overview of all bugs that have been fixed in 0.19.2.

v0.19.1 Final

This is a minor bug-fix release from 0.19.0 and includes some small regression fixes,
bug fixes and performance improvements.

See the v0.19.1 Whatsnew page for an overview of all bugs that have been fixed in 0.19.1.

v0.19.0 Final

This is a major release from 0.18.1 and includes a number of API changes, several new features, enhancements, 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
• .rolling() is now time-series aware, see here
• read_csv now supports parsing Categorical data, see here
• A function union_categorical has been added for combining categoricals, see here
• PeriodIndex now has its own period dtype, and changed to be more consistent with other Index classes. See here
• Sparse data structures gained enhanced support of int and bool dtypes, see here
• Comparison operations with Series no longer ignores the index, see here for an overview of the API changes.
• Introduction of a pandas development API for utility functions, see here.
• Deprecation of Panel4D and PanelND. We recommend to represent these types of n-dimensional data with the xarray package.
• Removal of the previously deprecated modules pandas.io.data, pandas.io.wb, pandas.tools.rplot.

See the Whatsnew file for more information.

v0.19.0rc1

RELEASE CANDIDATE

This is a major release from 0.18.1 and includes a number of API changes, several new features, enhancements, 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
• .rolling() is now time-series aware, see here
• read_csv now supports parsing Categorical data, see here
• A function union_categorical has been added for combining categoricals, see here
• PeriodIndex now has its own period dtype, and changed to be more consistent with other Index classes. See here
• Sparse data structures gained enhanced support of int and bool dtypes, see here
• Comparison operations with Series no longer ignores the index, see here for an overview of the API changes.
• Introduction of a pandas development API for utility functions, see here.
• Deprecation of Panel4D and PanelND. We recommend to represent these types of n-dimensional data with the xarray package.
• Removal of the previously deprecated modules pandas.io.data, pandas.io.wb, pandas.tools.rplot.

See the Whatsnew file for more information. Please report any issues here.

The release candidate can be installed with conda from our development channel (builds for osx-64, linux-64 and win-64 for Python 2.7 and Python 3.5 are all available):

conda install -c pandas pandas=0.19.0rc1

v0.18.1 Final

This is a minor release from 0.18.0 and includes a large number of bug fixes
along 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 when working with .rolling(..), .expanding(..) and .resample(..) per group, see here
• pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here
• Method chaining improvements, see here
• Custom business hour offset, see here
• Many bug fixes in the handling of sparse, see here
• Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger (:issue:13045).

You an install the latest version of pandas via conda:

conda install pandas -c conda-forge

v0.18.0 Final

This is a major release from 0.17.1 and includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version.

Highlights include:

• pandas >= 0.18.0 will no longer support compatibility with Python version 2.6 GH11273 and 3.3 GH7718
• Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here.
• Adding support for a RangeIndex as a specialized form of the Int64Index
  for memory savings, see here.
• API breaking .resample changes to make it more .groupby like, see here
• Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here
• The .to_xarray() function has been added for compatibility with the xarray package see here.
• The read_sas() function has been enhanced to read sas7bdat files, see here
• Addition of the .str.extractall() method, and API changes to the the .str.extract() method, and the.str.cat() method
• pd.test() top-level nose test runner is available GH4327

See the Whatsnew for much more information. Please report any issues here

best way to get this is to install via conda. Builds for osx-64,linux-64,win-64 for Python 2.7, Python 3.4 and Python 3.5 are all available.

conda install pandas