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Releases: pandas-dev/pandas

v0.20.2 Final

04 Jun 20:58
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This is a minor bug-fix release in the 0.20.x series and includes some small regression fixes,
bug fixes and performance improvements.
We recommend that all users upgrade to this version.

See the v0.20.2 Whatsnew page for an overview of all the bugs that have been fixed in 0.20.2.

v0.20.1 Final

05 May 17:16
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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

05 May 02:37
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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

04 May 15:10
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v0.20.0rc2 Pre-release
Pre-release

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

22 Apr 03:56
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v0.20.0rc1 Pre-release
Pre-release

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

24 Dec 16:47
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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:

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

03 Nov 15:29
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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

02 Oct 14:17
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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

07 Sep 20:50
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v0.19.0rc1 Pre-release
Pre-release

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

03 May 14:48
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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