PyPI · #40 most downloaded on PyPI

pandas

3.0.6547M downloads/mopandas-dev/pandas ↗New releases in your daily digest, changelog included.

Powerful data structures for data analysis, time series, and statistics

Last release 4 days ago
30 Sep 2026
Ships fairly regularly
a new release about every 6 weeks
Nearly every release is documented
notes for 60 of the last 60 stable releases
1 version withdrawn
withdrawn after publishing
17 years old
119 releases · first in 2009

Release timeline

119 releases since 2009

200920112013201520172019202120232025

20092026

One column per quarter.

Releases

1.0.030 Jan 2020
This is a major release from 0.25.3, and includes a number of API changes, new features, enhancements, and performance improvements along with a large
This is a major release from 0.25.3, and includes a number of API changes, new features, enhancements, and performance improvements along with a large number of bug fixes.

Highlights include

A redesigned website and documentation theme

Using Numba in rolling.apply

A new DataFrame method for converting to Markdown

A new scalar for missing values

Dedicated extension types for string and nullable boolean data

See the whatsnew for a list of all the changes.

The release can be installed from PyPI

python -m pip install --upgrade pandas

Or with conda from the defaults or conda-forge channels.

conda install pandas

Please report any issues with the release candidate on the pandas issue tracker.
Open source →
0.25.31 Nov 2019
This is a minor bug-fix release in the 0.25.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this ver
This is a minor bug-fix release in the 0.25.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the full whatsnew for a list of all the changes.

The release can be installed with conda from the defaults and conda-forge channels:

conda install pandas

Or via PyPI:

python3 -m pip install --upgrade pandas

Please report any issues with the release on the pandas issue tracker.
Open source →
0.25.219 Oct 2019
This is a minor bug-fix release in the 0.25.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this ver
This is a minor bug-fix release in the 0.25.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the full whatsnew for a list of all the changes.

The release can be installed with conda from the defaults and conda-forge channels:

conda install pandas

Or via PyPI:

python3 -m pip install --upgrade pandas

Please report any issues with the release on the pandas issue tracker.
Open source →
0.25.122 Aug 2019
This is a minor bug-fix release in the 0.25.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this ver
This is a minor bug-fix release in the 0.25.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the full whatsnew for a list of all the changes.

The release can be installed with conda from the defaults and conda-forge channels:

conda install pandas

Or via PyPI:

python -m pip install --upgrade pandas
Open source →
0.25.019 Jul 2019
This is a major release from 0.24.2 and includes a number of API changes, new features, enhancements, and performance improvements along with a large
This is a major release from 0.24.2 and includes a number of API changes, new features, enhancements, and performance improvements along with a large number of bug fixes.

Highlights include

Dropped Python 2 support

Groupby aggregation with relabeling

Better repr for MultiIndex

Better truncated repr for Series and DataFrame

Series.explode to split list-like values to rows

See the release notes for a full list of all the changes from 0.24.2.

The release can be installed with conda using the defaults or conda-forge channels

conda install pandas

Or via PyPI

python3 -m pip install --upgrade pandas

Please report any issues with the release on the pandas issue tracker.
Open source →
0.24.214 Mar 2019
This is a minor bug-fix release in the 0.24.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this ver
This is a minor bug-fix release in the 0.24.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the full whatsnew for a list of all the changes.

The release can be installed with conda from the defaults and conda-forge channels:

conda install pandas

Or via PyPI:

python -m pip install --upgrade pandas
Open source →
0.24.14 Feb 2019
This is a minor bug-fix release in the 0.24.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this ver
This is a minor bug-fix release in the 0.24.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the full whatsnew for a list of all the changes.

The release can be installed with conda from the defaults and conda-forge channels:

conda install pandas

Or via PyPI:

python -m pip install --upgrade pandas
Open source →
0.24.025 Jan 2019
This is a major release from 0.23.4 and includes a number of API changes, new features, enhancements, and performance improvements along with a large
This is a major release from 0.23.4 and includes a number of API changes, new features, enhancements, and performance improvements along with a large number of bug fixes.

Highlights include:

Optional Nullable Integer Support

New APIs for accessing the array backing a Series or Index

A new top-level pandas.array() method for creating arrays

Store Interval and Period data in a Series or DataFrame

Joining with two MultiIndexes

See the release notes for a full list of all the change from 0.23.4

The release candidate can be installed with conda using the defaults or conda-forge channels

conda install pandas

Or via PyPI

python3 -m pip install --upgrade pandas

Note that 0.24.x is the last series of releases to support Python 2.

Please report any issues with the release candidate on the pandas issue tracker.
Open source →
0.23.44 Aug 2018
This is a minor bug-fix release in the 0.23.x series and includes some small regression fixes and bug fixes. We recommend that all users upgrade to th
This is a minor bug-fix release in the 0.23.x series and includes some small regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the full whatsnew for a list of all the changes.

The release can be installed with conda from the default channel and conda-forge:

conda install pandas

Or via PyPI:

python -m pip install --upgrade pandas
Open source →
0.23.37 Jul 2018
This release fixes a build issue with the sdist for Python 3.7. There are no other changes.
This release fixes a build issue with the sdist for Python 3.7. There are no other changes.

Open source →
0.23.26 Jul 2018
This is a minor bug-fix release in the 0.23.x series and includes some regression fixes, bug fixes, and performance improvements. We recommend that al
This is a minor bug-fix release in the 0.23.x series and includes some regression fixes, bug fixes, and performance improvements. We recommend that all users upgrade to this version. See the full whatsnew for a list of all the changes.

The release can be installed with conda from the default channel and conda-forge::

conda install pandas

Or via PyPI:

python -m pip install --upgrade pandas
Open source →
0.23.113 Jun 2018
This is a minor bug-fix release in the 0.23.x series and includes some regression fixes, bug fixes, and performance improvements. We recommend that al
This is a minor bug-fix release in the 0.23.x series and includes some regression fixes, bug fixes, and performance improvements. We recommend that all users upgrade to this version. See the full whatsnew for a list of all the changes.

The release can be installed with conda from the default channel and conda-forge::

conda install pandas

Or via PyPI:

python -m pip install --upgrade pandas
Open source →
0.23.016 May 2018
This is a major release from 0.22.0 and includes a number of API changes, new features, enhancements, and performance improvements along with a large
This is a major release from 0.22.0 and includes a number of API changes, new features, enhancements, and performance improvements along with a large number of bug fixes.

Highlights include:

Round-trippable JSON format with 'table' orient

Instantiation from dicts respects order for Python 3.6+

Dependent column arguments for assign

Merging / sorting on a combination of columns and index levels

Extending Pandas with custom types

Excluding unobserved categories from groupby

See the full whatsnew for a list of all the changes.

The release candidate can be installed with conda from from conda-forge (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=0.23.0

Or via PyPI

python3 -m pip install --upgrade pandas

Updated conda packages will be available in the default channel shortly.
Open source →
0.22.031 Dec 2017Breaking
This is a major release from 0.21.1 and includes a single, API-breaking change. We recommend that all users upgrade to this version after carefully re…
This is a major release from 0.21.1 and includes a single, API-breaking change. We recommend that all users upgrade to this version after carefully reading the release note.

The only changes are:

The sum of an empty or all-NA Series is now 0

The product of an empty or all-NA Series is now 1

We've added a min_count parameter to .sum() and .prod() controlling the minimum number of valid values for the result to be valid. If fewer than min_count non-NA values are present, the result is NA. The default is 0. To return NaN, the 0.21 behavior, use min_count=1.

See the whatsnew for further explanation of all the places in the library this affects.
Open source →
0.21.113 Dec 2017
This is a minor bug-fix release in the 0.21.x series and includes some small regression fixes, bug fixes and performance improvements. We recommend th
This is a minor bug-fix release in the 0.21.x series and includes 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. This should resolve issues for users who relied implicitly on pandas to plot datetimes with matplotlib. See here

Improvements to the Parquet IO functions introduced in 0.21.0. See here

See the v0.21.1 Whatsnew overview for an extensive list of all the changes for 0.21.1.
Open source →
0.21.028 Oct 2017Breaking
Check the whatsnew for detailed changes, including backwards incompatible changes and deprecations. Please report any issues you find on the pandas is…
This is a major release from 0.20.3 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:

Integration with Apache Parquet, including a new top-level read_parquet function and a DataFrame.to_parquet method, see here.

New user-facing dtype pandas.api.types.CategoricalDtype for specifying categoricals independent of the data, see here.

The behavior of sum and prod on all-NaN Series/DataFrames is now consistent and no longer depends on whether bottleneck is installed, see here.

Compatibility fixes for pypy, see here.

Additions to the drop, reindex, and rename API to make them more consistent, see here

Addition of the new methods DataFrame.infer_objects (see here) and GroupBy.pipe (see here).

Indexing with a list of labels, where one or more of the labels is missing, is deprecated and will raise a KeyError in a future version, see here.

Check the whatsnew for detailed changes, including backwards incompatible changes and deprecations. Please report any issues you find on the pandas issue tracker.

Binary packages will be available in the defaults and conda-forge channels shortly.

conda install pandas

Wheels and a source distribution are available on PyPI.

pip install --upgrade pip setuptools pip install --upgrade --upgrade-strategy=only-if-needed pandas
Open source →
0.20.37 Jul 2017
This is a minor bug-fix release in the 0.20.x series and includes some small regression fixes and bug fixes. We recommend that all users upgrade to th
This is a minor bug-fix release in the 0.20.x series and includes some small regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the v0.20.3 Whatsnew page for an overview of all the bugs that have been fixed in 0.20.3.

Open source →
0.20.25 Jun 2017
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 th
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.

Open source →
0.20.15 May 2017
This is a minor release from 0.20.0 and includes a single change for backwards-compatibility with downstream projects using pandas' utils routines. Se
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
Open source →
0.20.05 May 2017Deprecated
This is a major release from 0.19.2 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along…
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.
Open source →
0.19.224 Dec 2016
This is a minor bug-fix release in the 0.19.x series and includes some small regression fixes, bug fixes and performance improvements.
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.
Open source →
0.19.13 Nov 2016
This is a minor bug-fix release from 0.19.0 and includes some small regression fixes, bug fixes and performance improvements.
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.

Open source →
0.19.02 Oct 2016Deprecated
Deprecation of Panel4D and PanelND. We recommend to represent these types of n-dimensional data with the xarray package.
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.
Open source →
0.18.15 May 2016
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 improvemen
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
Open source →
0.18.012 Mar 2016Deprecated
Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here
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
Open source →
0.17.120 Nov 2015
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
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
Open source →
0.17.09 Oct 2015Deprecated
Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see here
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
Open source →
0.16.213 Jun 2015
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 impro
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
Open source →
0.16.111 May 2015
This is a minor bug-fix release from 0.16.0 and includes a a large number of bug fixes along several new features, enhancements, and performance impro
This is a minor bug-fix release from 0.16.0 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:

Support for a CategoricalIndex, a category based index, see here

New section on how-to-contribute to pandas, see here

Revised "Merge, join, and concatenate" documentation, including graphical examples to make it easier to understand each operations, see here

New method sample for drawing random samples from Series, DataFrames and Panels. See here

The default Index printing has changed to a more uniform format, see here

BusinessHour datetime-offset is now supported, see here

Further enhancement to the .str accessor to make string operations easier, see here

See the full whatsnew here
Open source →
0.16.022 Mar 2015Breaking
Backwards incompatible change to Timedelta to conform the .seconds attribute with datetime.timedelta, see here
This is a major release from 0.15.2 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:

DataFrame.assign method, see here

Series.to_coo/from_coo methods to interact with scipy.sparse, see here

Backwards incompatible change to Timedelta to conform the .seconds attribute with datetime.timedelta, see here

Changes to the .loc slicing API to conform with the behavior of .ix see here

Changes to the default for ordering in the Categorical constructor, see here

Enhancement to the .str accessor to make string operations easier, see here

The pandas.tools.rplot, pandas.sandbox.qtpandas and pandas.rpy modules are deprecated. We refer users to external packages like seaborn, pandas-qt and rpy2 for similar or equivalent functionality, see here for more detail.

See the Whatsnew for an extensive list of all API changes, enhancements and bugs that have been fixed in 0.16.0.
Open source →
0.15.211 Dec 2014
This is a minor release from 0.15.1 and includes a small number of API changes, several new features, enhancements, and performance improvements along
This is a minor release from 0.15.1 and includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes.

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

Open source →
0.15.18 Nov 2014
This is a minor release from 0.15.0 and includes a small number of API changes, several new features, enhancements, and performance improvements along
This is a minor release from 0.15.0 and includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes.

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

Open source →
0.15.019 Oct 2014
This is a major release from 0.14.1 and includes a number of API changes, several new features, enhancements, and performance improvements along with
This is a major release from 0.14.1 and includes a number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes.

Highlights include:

Drop support for numpy < 1.7.0

The Categorical type was integrated as a first-class pandas type

New scalar type Timedelta, and a new index type TimedeltaIndex

New DataFrame default display for df.info() to include memory usage

New datetimelike properties accessor .dt for Series

Split indexing documentation into Indexing and Selecting Data and MultiIndex / Advanced Indexing

Split out string methods documentation into Working with Text Data

read_csv will now by default ignore blank lines when parsing

API change in using Indexes in set operations

Internal refactoring of the Index class to no longer sub-class ndarray

dropping support for PyTables less than version 3.0.0, and numexpr less than version 2.1

See the Whatsnew for much more information. Please report any issues here
Open source →
0.14.110 Jul 2014
This is a minor release from 0.14.0 and includes a small number of API changes, several new features, enhancements, and performance improvements along
This is a minor release from 0.14.0 and includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes.

Highlights include:

New methods pandas.DataFrame.select_dtypes to select columns based on the dtype and pandas.Series.sem to calculate the standard error of the mean.

Support for dateutil timezones.

Support for ignoring full line comments in the pandas.read_csv text parser.

New documentation section on `Options and Settings```.

Lots of bug fixes.
Open source →
0.14.030 May 2014
Announcing v0.14.0, a major release from 0.13.1. This release includes a small number of API changes, several new features, enhancements, and performa
Announcing v0.14.0, a major release from 0.13.1. This release 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

Officially support Python 3.4

SQL interfaces updated to use sqlalchemy

Display interface changes

MultiIndexing Using Slicers

Ability to join a singly-indexed DataFrame with a multi-indexed DataFrame

More consistency in groupby results and more flexible groupby specifications

Holiday calendars are now supported in CustomBusinessDay

Several improvements in plotting functions, including: hexbin, area and pie plots

Performance doc section on I/O operations
Open source →
0.13.19 Feb 2014
Nothing published for this version
0.13.014 Jan 2014
Includes hotfix for 0.13.0, with setup.py changes from #5844. Fixing an installation error for users who do not have cython installed.
Includes hotfix for 0.13.0, with setup.py changes from #5844. Fixing an installation error for users who do not have cython installed.

Open source →
0.12.024 Jul 2013
Nothing published for this version
0.11.023 Apr 2013
Nothing published for this version
0.10.122 Jan 2013
Nothing published for this version
0.10.017 Dec 2012
Nothing published for this version
0.9.115 Nov 2012
Nothing published for this version
0.9.08 Oct 2012
Nothing published for this version
0.8.122 Jul 2012
Nothing published for this version
0.8.029 Jun 2012
Nothing published for this version
0.7.312 Apr 2012
Nothing published for this version
0.7.216 Mar 2012
Nothing published for this version
0.7.129 Feb 2012
Nothing published for this version
0.7.09 Feb 2012
Nothing published for this version
0.6.114 Dec 2011
Nothing published for this version
0.6.026 Nov 2011
Nothing published for this version
0.5.025 Oct 2011
Nothing published for this version
0.4.39 Oct 2011
Nothing published for this version
0.4.23 Oct 2011
Nothing published for this version
0.4.126 Sept 2011
Nothing published for this version
0.4.012 Sept 2011
Nothing published for this version
0.3.020 Feb 2011
Nothing published for this version
0.218 May 2010
Nothing published for this version
0.125 Dec 2009
Nothing published for this version

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Releases

1.0.030 Jan 2020

This is a major release from 0.25.3, and includes a number of API changes, new features, enhancements, and performance improvements along with a large

This is a major release from 0.25.3, and includes a number of API changes, new features, enhancements, and performance improvements along with a large number of bug fixes.

Highlights include

A redesigned website and documentation theme
Using Numba in rolling.apply
A new DataFrame method for converting to Markdown
A new scalar for missing values
Dedicated extension types for string and nullable boolean data

See the whatsnew for a list of all the changes.

The release can be installed from PyPI

python -m pip install --upgrade pandas

Or with conda from the defaults or conda-forge channels.

conda install pandas

Please report any issues with the release candidate on the pandas issue tracker.