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

v0.18.0rc2

RELEASE CANDIDATE 2

THIS IS NOT A PRODUCTION RELEASE

Compared to RC1, this includes the update to read_sas as well as fixes for float indexing.

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 from our development channel. Builds for osx-64,linux-64,win-64 for Python 2.7 and Python 3.5 are all available.

conda install pandas=v0.18.0rc2 -c pandas

v0.18.0rc1

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.
• 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 from our development channel. Builds for osx-64,linux-64,win-64 for Python 2.7 and Python 3.5 are all available.

conda install pandas=v0.18.0rc1 -c pandas

v0.17.1 Final

We are proud to announce that pandas has become a sponsored project of the NUMFocus organization
This will help ensure the success of development of pandas as a world-class open-source project.

This is a minor bug-fix release from 0.17.0 and includes a large number of
bug fixes along several new features, enhancements, and performance improvements.
We recommend that all users upgrade to this version.

Highlights include:

• Support for Conditional HTML Formatting, see here
• Releasing the GIL on the csv reader & other ops, see here
• Fixed regression in DataFrame.drop_duplicates from 0.16.2, causing incorrect results on integer values see here

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

You an install the latest version of pandas via conda:

conda install pandas -u pandas

v0.17.0 Final

This is a major release from 0.16.2 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:

• Release the Global Interpreter Lock (GIL) on some cython operations, see here
• Plotting methods are now available as attributes of the .plot accessor, see here
• The sorting API has been revamped to remove some long-time inconsistencies, see here
• Support for a datetime64[ns] with timezones as a first-class dtype, see here
• The default for to_datetime will now be to raise when presented with unparseable formats, previously this would return the original input, see here
• The default for dropna in HDFStore has changed to False, to store by default all rows even if they are all NaN, see here
• Datetime accessor (dt) now supports Series.dt.strftime to generate formatted strings for datetime-likes, and Series.dt.total_seconds to generate each duration of the timedelta in seconds. See here
• Period and PeriodIndex can handle multiplied freq like 3D, which corresponding to 3 days span. See here
• Development installed versions of pandas will now have PEP440 compliant version strings GH9518
• Development support for benchmarking with the Air Speed Velocity library GH8361
• Support for reading SAS xport files, see here
• Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see here
• Display format with plain text can optionally align with Unicode East Asian Width, see here
• Compatibility with Python 3.5 GH11097
• Compatibility with matplotlib 1.5.0 GH11111

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

You an install the latest version of pandas via conda:

conda install pandas -u pandas

v0.17.0rc2

RELEASE CANDIDATE 2

Since release candidate 1:

• compat for Python 3.5
• compat for matplotlib 1.5.0
• .convert_objects is now restored to the original, and is deprecated

This is a major release from 0.16.2 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:

• Release the Global Interpreter Lock (GIL) on some cython operations, see here
• Plotting methods are now available as attributes of the .plot accessor, see here
• The sorting API has been revamped to remove some long-time inconsistencies, see here
• Support for a datetime64[ns] with timezones as a first-class dtype, see here
• The default for to_datetime will now be to raise when presented with unparseable formats, previously this would return the original input, see here
• The default for dropna in HDFStore has changed to False, to store by default all rows even if they are all NaN, see here
• Datetime accessor (dt) now supports Series.dt.strftime to generate formatted strings for datetime-likes, and Series.dt.total_seconds to generate each duration of the timedelta in seconds. See here
• Period and PeriodIndex can handle multiplied freq like 3D, which corresponding to 3 days span. See here
• Development installed versions of pandas will now have PEP440 compliant version strings GH9518
• Development support for benchmarking with the Air Speed Velocity library GH8361
• Support for reading SAS xport files, see here
• Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see here
• Display format with plain text can optionally align with Unicode East Asian Width, see here
• Compatibility with Python 3.5 GH11097
• Compatibility with matplotlib 1.5.0 GH11111

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

best way to get this is to install via conda from our development channel. 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 -c pandas

v0.17.0rc1

RELEASE CANDIDATE 1

This is a major release from 0.16.2 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:

• Release the Global Interpreter Lock (GIL) on some cython operations, see here
• Plotting methods are now available as attributes of the .plot accessor, see here
• The sorting API has been revamped to remove some long-time inconsistencies, see here
• Support for a datetime64[ns] with timezones as a first-class dtype, see here
• The default for to_datetime will now be to raise when presented with unparseable formats, previously this would return the original input, see here
• The default for dropna in HDFStore has changed to False, to store by default all rows even if they are all NaN, see here
• Datetime accessor (dt) now supports Series.dt.strftime to generate formatted strings for datetime-likes, and Series.dt.total_seconds to generate each duration of the timedelta in seconds. See here
• Period and PeriodIndex can handle multiplied freq like 3D, which corresponding to 3 days span. See here
• Development installed versions of pandas will now have PEP440 compliant version strings GH9518
• Development support for benchmarking with the Air Speed Velocity library GH8361
• Support for reading SAS xport files, see here
• Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see here

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

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

conda install pandas -c pandas

v0.16.2 Final

This is a minor bug-fix release from 0.16.1 and includes a a large number of
bug fixes along several new features, enhancements, and performance improvements.
We recommend that all users upgrade to this version.

Highlights include:

• A new pipe method, see here
• Documentation on how to use numba with pandas, see here

See the full whatsnew