GitHub repository: pandas-dev/pandas
Description: Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Topics: alignment, data-analysis, data-science, flexible, pandas, python

Pandas 2.2.0rc0: tag_name: v2.2.0rc0
body: We are pleased to announce a release candidate for pandas 2.2.0. If all goes well, we'll release pandas 2.2.0 in about two weeks.

See the [whatsnew](https://pandas.pydata.org/pandas-docs/version/2.2.0rc0/whatsnew/v2.2.0.html) for a list of all the changes.

The release will be available on conda-forge and PyPI.

The release can be installed from PyPI

python -m pip install --upgrade --pre pandas==2.2.0rc0
Or from conda-forge

conda install -c conda-forge/label/pandas_rc pandas==2.2.0rc0
Please report any issues with the release candidate on the pandas issue tracker.
Pandas 2.1.4: tag_name: v2.1.4
body: This is a patch release in the 2.1.x series and includes some regression and bug fixes, and a security fix. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/2.1.4/whatsnew/v2.1.4.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 2.1.3: tag_name: v2.1.3
body: This is a patch release in the 2.1.x series and includes some regression and bug fixes, and a security fix. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/2.1.3/whatsnew/v2.1.3.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 2.1.2: tag_name: v2.1.2
body: This is a patch release in the 2.1.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/2.1.2/whatsnew/v2.1.2.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 2.1.1: tag_name: v2.1.1
body: This is a patch release in the 2.1.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/2.1.1/whatsnew/v2.1.1.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 2.1.0: tag_name: v2.1.0
body: We are pleased to announce the release of pandas 2.1.0.
This release includes some new features, bug fixes, and performance improvements. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/2.1.0/whatsnew/v2.1.0.html) for a list of all the changes.
Pandas 2.1.0 supports Python 3.9 and higher.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 2.1.0rc0: tag_name: v2.1.0rc0
body: We are pleased to announce a release candidate for pandas 2.1.0. If all goes well, we'll release pandas 2.1.0 in about two weeks.

See the [whatsnew][0] for a list of all the changes.

The release will be available on conda-forge and PyPI.

The release can be installed from PyPI

    python -m pip install --upgrade --pre pandas==2.1.0rc0

Or from conda-forge

    conda install -c conda-forge/label/pandas_rc pandas==2.1.0rc0

Please report any issues with the release candidate on the pandas issue tracker.

[0]: https://pandas.pydata.org/pandas-docs/version/2.1.0rc0/whatsnew/v2.1.0.html
Pandas 2.0.3: tag_name: v2.0.3
body: This is a patch release in the 2.0.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/2.0.3/whatsnew/v2.0.3.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 2.0.2: tag_name: v2.0.2
body: This is a patch release in the 2.0.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/2.0.2/whatsnew/v2.0.2.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 2.0.1: tag_name: v2.0.1
body: This is a patch release in the 2.0.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/2.0.1/whatsnew/v2.0.1.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 2.0.0: tag_name: v2.0.0
body: We are pleased to announce the release of pandas 2.0.0, a major release from the pandas 1 series. This release includes some new features, bug fixes, and performance improvements, as well as possible breaking changes. It is recommended that users with existing code upgrade to pandas 1.5.3 before they upgrade to pandas 2, and make sure their code does not generate FutureWarning or DeprecationWarning messages.

See the [whatsnew][0] for a list of all the changes.

The release will be available on conda-forge and PyPI.

The release can be installed from PyPI

    python -m pip install --upgrade pandas==2.0.0

Or from conda-forge

    mamba install -c conda-forge pandas==2.0.0

Please report any issues with the release candidate on the [pandas issue tracker](https://github.com/pandas-dev/pandas/issues/new/choose).

[0]: https://pandas.pydata.org/pandas-docs/version/2.0/whatsnew/v2.0.0.html
Pandas 2.0.0rc1: tag_name: v2.0.0rc1
body: We are pleased to announce the second release candidate for pandas 2.0.0. If all goes well, we'll release pandas 2.0.0 in about two weeks.

See the [whatsnew][0] for a list of all the changes.

The release will be available on conda-forge and PyPI.

The release can be installed from PyPI

    python -m pip install --upgrade --pre pandas==2.0.0rc1

Or from conda-forge

    conda install -c conda-forge/label/pandas_rc pandas==2.0.0rc1

Please report any issues with the release candidate on the pandas issue tracker.

[0]: https://pandas.pydata.org/pandas-docs/version/2.0/whatsnew/v2.0.0.html
Pandas 2.0.0rc0: tag_name: v2.0.0rc0
body: We are pleased to announce a release candidate for pandas 2.0.0. If all goes well, we'll release pandas 2.0.0 in about two weeks.

See the [whatsnew][0] for a list of all the changes.

The release will be available on conda-forge and PyPI.

The release can be installed from PyPI

    python -m pip install --upgrade --pre pandas==2.0.0rc0

Or from conda-forge

    conda install -c conda-forge/label/pandas_rc pandas==2.0.0rc0

Please report any issues with the release candidate on the pandas issue tracker.

[0]: https://pandas.pydata.org/pandas-docs/version/2.0/whatsnew/v2.0.0.html
Pandas 1.5.3: tag_name: v1.5.3
body: This is a patch release in the 1.5.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.5.3/whatsnew/v1.5.3.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 1.5.2: tag_name: v1.5.2
body: This is a patch release in the 1.5.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.5.2/whatsnew/v1.5.2.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 1.5.1: tag_name: v1.5.1
body: This is a patch release in the 1.5.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.5.1/whatsnew/v1.5.1.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 1.5.0: tag_name: v1.5.0
body: This release includes some new features, bug fixes, and performance improvements. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.5.0/whatsnew/v1.5.0.html) for a list of all the changes. pandas 1.5.0 supports Python 3.8 and higher.

The release will be available on the defaults and conda-forge channels:

`conda install -c conda-forge pandas`

Or via PyPI:

`python3 -m pip install --upgrade pandas`

Please report any issues with the release on the [pandas issue tracker](https://github.com/pandas-dev/pandas/issues).
Pandas 1.4.4: tag_name: v1.4.4
body: This is a patch release in the 1.4.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.4.4/whatsnew/v1.4.4.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Thanks to all the contributors who made this release possible.
Pandas 1.5.0rc0: tag_name: v1.5.0rc0
body: We are pleased to announce a release candidate for pandas 1.5.0. If all goes well, we'll release pandas 1.5.0 in about two weeks.

See the [whatsnew][0] for a list of all the changes.

The release will be available on conda-forge and PyPI.

The release can be installed from PyPI

    python -m pip install --upgrade --pre pandas==1.5.0rc0

Or from conda-forge

    conda install -c conda-forge/label/pandas_rc pandas==1.5.0rc0

Please report any issues with the release candidate on the pandas issue tracker.

[0]: https://pandas.pydata.org/pandas-docs/version/1.5/whatsnew/v1.5.0.html
Pandas 1.4.3: tag_name: v1.4.3
body: This is a patch release in the 1.4.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.4.3/whatsnew/v1.4.3.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.4.2: tag_name: v1.4.2
body: This is a patch release in the 1.4.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.4.2/whatsnew/v1.4.2.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.4.1: tag_name: v1.4.1
body: This is the first patch release in the 1.4.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.4.1/whatsnew/v1.4.1.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.4.0: tag_name: v1.4.0
body: This release includes some new features, bug fixes, and performance improvements. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.4.0/whatsnew/v1.4.0.html) for a list of all the changes. pandas 1.4.0 supports Python 3.8 and higher.

The release will be available on the defaults and conda-forge channels:

    conda install -c conda-forge pandas

Or via PyPI:

    python3 -m pip install --upgrade pandas

Please report any issues with the release on the [pandas issue tracker](https://github.com/pandas-dev/pandas/issues).

Pandas 1.4.0rc0: tag_name: v1.4.0rc0
body: We are pleased to announce a release candidate for pandas 1.4.0. If all goes well, we'll release pandas 1.4.0 in about two weeks.

See the [whatsnew][0] for a list of all the changes. pandas 1.4.0 supports Python 3.8 and higher.

The release will be available on conda-forge and PyPI.

The release can be installed from PyPI

    python -m pip install --upgrade --pre pandas==1.4.0rc0

Or from conda-forge

    conda install -c conda-forge/label/pandas_rc pandas==1.4.0rc0

Please report any issues with the release candidate on the pandas issue tracker.

[0]: https://pandas.pydata.org/pandas-docs/version/1.4/whatsnew/v1.4.0.html
Pandas 1.3.5: tag_name: v1.3.5
body: This is a patch release in the 1.3.x series and includes some regression fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.3.5/whatsnew/v1.3.5.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.3.4: tag_name: v1.3.4
body: This is a patch release in the 1.3.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.3.4/whatsnew/v1.3.4.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.3.3: tag_name: v1.3.3
body: This is a patch release in the 1.3.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.3.3/whatsnew/v1.3.3.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.3.2: tag_name: v1.3.2
body: This is a patch release in the 1.3.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.3.2/whatsnew/v1.3.2.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.3.1: tag_name: v1.3.1
body: This is the first patch release in the 1.3.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.3.1/whatsnew/v1.3.1.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.3.0: tag_name: v1.3.0
body: This release includes some new features, bug fixes, and performance improvements. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.3.0/whatsnew/v1.3.0.html) for a list of all the changes.

The release will be available on the defaults and conda-forge channels:

    conda install -c conda-forge pandas

Or via PyPI:

    python3 -m pip install --upgrade pandas

Please report any issues with the release on the [pandas issue tracker](https://github.com/pandas-dev/pandas/issues).

Pandas 1.2.5: tag_name: v1.2.5
body: This is a patch release in the 1.2.x series and includes some regression fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.2.5/whatsnew/v1.2.5.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.3.0rc1: tag_name: v1.3.0rc1
body: We are pleased to announce a release candidate for pandas 1.3.0. If all goes well, we'll release pandas 1.3.0 in about two weeks.

See the [whatsnew][0] for a list of all the changes.

The release will be available on conda-forge and PyPI.

The release can be installed from PyPI

    python -m pip install --upgrade --pre pandas==1.3.0rc1

Or from conda-forge

    conda install -c conda-forge/label/pandas_rc pandas==1.3.0rc1

Please report any issues with the release candidate on the pandas issue tracker.

[0]: https://pandas.pydata.org/pandas-docs/version/1.3/whatsnew/v1.3.0.html
Pandas 1.2.4: tag_name: v1.2.4
body: This is a patch release in the 1.2.x series and includes some regression fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.2.4/whatsnew/v1.2.4.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.2.3: tag_name: v1.2.3
body: This is a patch release in the 1.2.x series and includes some regression fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.2.3/whatsnew/v1.2.3.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.2.2: tag_name: v1.2.2
body: This is a patch release in the 1.2.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.2.2/whatsnew/v1.2.2.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.2.1: tag_name: v1.2.1
body: This is the first patch release in the 1.2.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.2.1/whatsnew/v1.2.1.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.2.0: tag_name: v1.2.0
body: This release includes some new features, bug fixes, and performance improvements. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.2.0/whatsnew/v1.2.0.html) for a list of all the changes.

The release will be available on the defaults and conda-forge channels:

    conda install -c conda-forge pandas

Or via PyPI:

    python3 -m pip install --upgrade pandas

Please report any issues with the release on the [pandas issue tracker](https://github.com/pandas-dev/pandas/issues).

Pandas 1.2.0rc0: tag_name: v1.2.0rc0
body: This is the first release candidate for 1.2.0rc0. If all goes well, we'll release pandas 1.2.0 in about two weeks.

See the [whatsnew][0] for a list of all the changes.

The release can be installed from PyPI

    python -m pip install --upgrade --pre pandas==1.2.0rc0

Or from conda-forge

    conda install -c conda-forge/label/pandas_rc pandas==1.2.0rc0

Please report any issues with the release candidate on the pandas issue tracker.

[0]: https://pandas.pydata.org/pandas-docs/version/1.2.0/whatsnew/v1.2.0.html
Pandas 1.1.5: tag_name: v1.1.5
body: This is a minor bug-fix release in the 1.1.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.1.5/whatsnew/v1.1.5.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.1.4: tag_name: v1.1.4
body: This is a minor bug-fix release in the 1.1.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.1.4/whatsnew/v1.1.4.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.1.3: tag_name: v1.1.3
body: This is a minor bug-fix release in the 1.1.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.1.3/whatsnew/v1.1.3.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.1.2: tag_name: v1.1.2
body: This is a minor bug-fix release in the 1.1.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.1.2/whatsnew/v1.1.2.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.1.1: tag_name: v1.1.1
body: This is a minor bug-fix release in the 1.1.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.1.1/whatsnew/v1.1.1.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.1.0: tag_name: v1.1.0
body: This is a minor release which includes some new features, bug fixes, and performance improvements. We recommend that all users upgrade to this version.

See the [whatsnew](https://pandas.pydata.org/pandas-docs/version/1.1.1/whatsnew/v1.1.0.html) for a list of all the changes.

The release can be installed from PyPI

    python -m pip install --upgrade pandas==1.1.0

Or from conda-forge

    conda install -c conda-forge pandas==1.1.0

Please report any issues with the release candidate on the pandas issue tracker.

[0]: https://pandas.pydata.org/pandas-docs/version/1.1.0/
Pandas 1.1.0rc0: tag_name: v1.1.0rc0
body: This is the first release candidate for 1.1.0rc0. If all goes well, we'll release pandas 1.1.0 in about two weeks.

See the [whatsnew][0] for a list of all the changes.

The release can be installed from PyPI

    python -m pip install --upgrade --pre pandas==1.1.0rc0

Or from conda-forge

    conda install -c conda-forge/label/pandas_rc pandas==1.1.0rc0

Please report any issues with the release candidate on the pandas issue tracker.

[0]: https://pandas.pydata.org/pandas-docs/version/1.1.0/
Pandas 1.0.5: tag_name: v1.0.5
body: This is a minor bug-fix release in the 1.0.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/pandas-docs/version/1.0.5/whatsnew/v1.0.5.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.0.4: tag_name: v1.0.4
body: This is a minor bug-fix release in the 1.0.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/docs/whatsnew/v1.0.4.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.0.3: tag_name: v1.0.3
body: This is a minor bug-fix release in the 1.0.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/docs/whatsnew/v1.0.3.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.0.2: tag_name: v1.0.2
body: This is a minor bug-fix release in the 1.0.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/docs/whatsnew/v1.0.2.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.0.1: tag_name: v1.0.1
body: This is a minor bug-fix release in the 1.0.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.

See the [full whatsnew](https://pandas.pydata.org/docs/whatsnew/v1.0.1.html) for a list of all the changes.

The release will be available on 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](https://github.com/pandas-dev/pandas/issues).

Pandas 1.0.0: tag_name: v1.0.0
body: 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`](https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#using-numba-in-rolling-apply-and-expanding-apply)
* [A new DataFrame method for converting to Markdown](https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#converting-to-markdown)
* [A new scalar for missing values](https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#experimental-na-scalar-to-denote-missing-values)
* Dedicated extension types for [string](https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#dedicated-string-data-type) and
  [nullable boolean](https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#boolean-data-type-with-missing-values-support) data

See the [whatsnew](https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html) 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](https://github.com/pandas-dev/pandas/issues).
v1.0.0rc0: tag_name: v1.0.0rc0
body: This is the first release candidate for 1.0.0. If all goes well, we'll release pandas 1.0.0 in about two weeks.

Highlights include

* [A new scalar for missing values](https://dev.pandas.io/docs/whatsnew/v1.0.0.html#experimental-na-scalar-to-denote-missing-values)
* Dedicated extension types for [string](https://dev.pandas.io/docs/whatsnew/v1.0.0.html#dedicated-string-data-type) and
  [nullable boolean](https://dev.pandas.io/docs/whatsnew/v1.0.0.html#boolean-data-type-with-missing-values-support) data
* [Using Numba in `rolling.apply`](https://dev.pandas.io/docs/whatsnew/v1.0.0.html#using-numba-in-rolling-apply)
* A redesigned website and documentation theme

See the [whatsnew](https://dev.pandas.io/docs/whatsnew/v1.0.0.html) for a list of all the
changes.

The release can be installed from PyPI

   python -m pip install --upgrade --pre pandas==1.0.0rc0

Or from conda-forge

    conda install -c conda-forge/label/rc pandas==1.0.0rc0

Please report any issues with the release candidate on the pandas
[issue tracker](https://github.com/pandas-dev/pandas/issues).


v0.25.3: tag_name: v0.25.3
body: 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](https://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.3.html) 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](https://github.com/pandas-dev/pandas/issues).

v0.25.2: tag_name: v0.25.2
body: 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](https://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.2.html) 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](https://github.com/pandas-dev/pandas/issues).

v0.25.1: tag_name: v0.25.1
body: 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](http://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.1.html) 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

Pandas 0.25.0: tag_name: v0.25.0
body: 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](https://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.0.html#groupby-aggregation-with-relabeling)
- [Better repr for MultiIndex](https://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.0.html#better-repr-for-multiindex)
- [Better truncated repr for Series and DataFrame](https://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.0.html#shorter-truncated-repr-for-series-and-dataframe)
- [Series.explode to split list-like values to rows](https://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.0.html#series-explode-to-split-list-like-values-to-rows)

See the [release notes](https://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.0.html) 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](https://github.com/pandas-dev/pandas/issues).
v0.25.0rc0: tag_name: v0.25.0rc0
body: 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](https://dev.pandas.io/whatsnew/v0.25.0.html#groupby-aggregation-with-relabeling)
- [Better repr for MultiIndex](https://dev.pandas.io/whatsnew/v0.25.0.html#better-repr-for-multiindex)
- [Better truncated repr for Series and DataFrame](https://dev.pandas.io/whatsnew/v0.25.0.html#shorter-truncated-repr-for-series-and-dataframe)

See the [release notes](https://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.0.html) for a full list of all the change from 0.24.2.

The release candidate can be installed with conda using the conda-forge channel

    conda install -c conda-forge/label/rc pandas=0.25.0rc0

Or via PyPI

    python3 -m pip install --upgrade --pre pandas

Please report any issues with the release candidate on the [pandas issue tracker](https://github.com/pandas-dev/pandas/issues).
v0.24.2: tag_name: v0.24.2
body: 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][1] 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

[1]: http://pandas.pydata.org/pandas-docs/version/0.24/whatsnew/v0.24.2.html
v0.24.1: tag_name: v0.24.1
body: 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][1] 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

[1]: http://pandas.pydata.org/pandas-docs/version/0.24.1/whatsnew/v0.24.1.html
Pandas 0.24.0: tag_name: v0.24.0
body: 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][1]
- [New APIs for accessing the array backing a Series or Index][2]
- [A new top-level ``pandas.array()`` method for creating arrays][3]
- [Store Interval and Period data in a Series or DataFrame][4]
- [Joining with two MultiIndexes][5]

See the [release notes][6] 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][7].


[1]: http://pandas.pydata.org/pandas-docs/version/0.24/whatsnew/v0.24.0.html#optional-integer-na-support
[2]: http://pandas.pydata.org/pandas-docs/version/0.24/whatsnew/v0.24.0.html#accessing-the-values-in-a-series-or-index
[3]: http://pandas.pydata.org/pandas-docs/version/0.24/whatsnew/v0.24.0.html#array
[4]: http://pandas.pydata.org/pandas-docs/version/0.24/whatsnew/v0.24.0.html#storing-interval-and-period-data-in-series-and-dataframe
[5]: http://pandas.pydata.org/pandas-docs/version/0.24/whatsnew/v0.24.0.html#joining-with-two-multi-indexes
[6]: http://pandas.pydata.org/pandas-docs/version/0.24/whatsnew/v0.24.0.html
[7]: https://github.com/pandas-dev/pandas/issues
v0.24.0rc1: tag_name: v0.24.0rc1
body: *This is the first release candidate for 0.24.0.*

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][1]
- [New APIs for accessing the array backing a Series or Index][2]
- [A new top-level ``pandas.array()`` method for creating arrays][3]
- [Store Interval and Period data in a Series or DataFrame][4]
- [Joining with two MultiIndexes][5]

See the [release notes][6] for a full list of all the change from 0.23.4

The release candidate can be installed with conda from from conda-forge

    conda install -c conda-forge/label/rc pandas=0.24.0rc1

Or via PyPI

    python3 -m pip install --upgrade --pre 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][7].


[1]: http://pandas.pydata.org/pandas-docs/version/0.24.0rc1/whatsnew/v0.24.0.html#optional-integer-na-support
[2]: http://pandas.pydata.org/pandas-docs/version/0.24.0rc1/whatsnew/v0.24.0.html#accessing-the-values-in-a-series-or-index
[3]: http://pandas.pydata.org/pandas-docs/version/0.24.0rc1/whatsnew/v0.24.0.html#array
[4]: http://pandas.pydata.org/pandas-docs/version/0.24.0rc1/whatsnew/v0.24.0.html#storing-interval-and-period-data-in-series-and-dataframe
[5]: http://pandas.pydata.org/pandas-docs/version/0.24.0rc1/whatsnew/v0.24.0.html#joining-with-two-multi-indexes
[6]: http://pandas.pydata.org/pandas-docs/version/0.24.0rc1/whatsnew/v0.24.0.html
[7]: https://github.com/pandas-dev/pandas/issues
v0.23.4: tag_name: v0.23.4
body: 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](https://pandas.pydata.org/pandas-docs/version/0.23.4/whatsnew.html) 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



v0.23.3: tag_name: v0.23.3
body: This release fixes a build issue with the sdist for Python 3.7.
There are no other changes.
v0.23.2: tag_name: v0.23.2
body: 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](https://pandas.pydata.org/pandas-docs/version/0.23.2/whatsnew.html) 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


v0.23.1: tag_name: v0.23.1
body: 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](https://pandas.pydata.org/pandas-docs/version/0.23.1/whatsnew.html#v0-23-1) 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
v0.23.0: tag_name: v0.23.0
body: 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](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#json-read-write-round-trippable-with-orient-table)
- [Instantiation from dicts respects order for Python 3.6+](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#instantation-from-dicts-preserves-dict-insertion-order-for-python-3-6)
- [Dependent column arguments for assign](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#assign-accepts-dependent-arguments)
- [Merging / sorting on a combination of columns and index levels](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#merging-on-a-combination-of-columns-and-index-levels)
- [Extending Pandas with custom types](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#extending-pandas-with-custom-types-experimental)
- [Excluding unobserved categories from groupby](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#categorical-groupers-has-gained-an-observed-keyword)

See the [full whatsnew][2] 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.

[1]: https://github.com/pandas-dev/pandas/issues
[2]: https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#v0-23-0
v0.23.0rc2: tag_name: v0.23.0rc2
body: *This is the first public release candidate for pandas 0.23.0*

This is a major release from 0.23.0 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](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#json-read-write-round-trippable-with-orient-table)
- [Instantiation from dicts respects order for Python 3.6+](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#instantation-from-dicts-preserves-dict-insertion-order-for-python-3-6)
- [Dependent column arguments for assign](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#assign-accepts-dependent-arguments)
- [Merging / sorting on a combination of columns and index levels](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#merging-on-a-combination-of-columns-and-index-levels)
- [Extending Pandas with custom types](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#extending-pandas-with-custom-types-experimental)
- [Excluding unobserved categories from groupby](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#categorical-groupers-has-gained-an-observed-keyword)

See the [full whatsnew][2] for a list of all the changes.

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 conda-forge --label=rc pandas=0.23.0rc2

Or via PyPI

    python3 -m pip install --pre --upgrade pandas==0.23.0rc2

[1]: https://github.com/pandas-dev/pandas/issues
[2]: https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#v0-23-0
v0.23.0rc1: tag_name: v0.23.0rc1
body: *This is the first release candidate for pandas 0.23.0*

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](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#json-read-write-round-trippable-with-orient-table)
- [Instantiation from dicts respects order for Python 3.6+](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#instantation-from-dicts-preserves-dict-insertion-order-for-python-3-6)
- [Dependent column arguments for assign](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#assign-accepts-dependent-arguments)
- [Merging / sorting on a combination of columns and index levels](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#merging-on-a-combination-of-columns-and-index-levels)
- [Extending Pandas with custom types](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#extending-pandas-with-custom-types-experimental)
- [Excluding unobserved categories from groupby](https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#categorical-groupers-has-gained-an-observed-keyword)

See the [full whatsnew][2] for a list of all the changes.

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 conda-forge --label=rc pandas=0.23.0rc1

Or via PyPI

    python3 -m pip install --pre --upgrade pandas

[1]: https://github.com/pandas-dev/pandas/issues
[2]: https://pandas.pydata.org/pandas-docs/version/0.23.0/whatsnew.html#v0-23-0

v0.22.0 Final: tag_name: v0.22.0
body: 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](https://pandas.pydata.org/pandas-docs/version/0.22.0/whatsnew.html#whatsnew-0220) for further explanation of all the places in the library this affects.

v0.21.1 Final: tag_name: v0.21.1
body: 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](https://pandas.pydata.org/pandas-docs/version/0.21.1/whatsnew.html#restore-matplotlib-datetime-converter-registration)
- Improvements to the Parquet IO functions introduced in 0.21.0. See
  [here](https://pandas.pydata.org/pandas-docs/version/0.21.1/whatsnew.html#improvements-to-the-parquet-io-functionality)

See the [v0.21.1 Whatsnew](https://pandas.pydata.org/pandas-docs/version/0.21.1/whatsnew.html#improvements-to-the-parquet-io-functionality) overview for an extensive list
of all the changes for 0.21.1.
v0.21.0 Final: tag_name: v0.21.0
body: 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](https://parquet.apache.org/), including a new top-level [`read_parquet`](http://pandas.pydata.org/pandas-docs/version/0.21/generated/pandas.read_parquet.html#pandas.read_parquet) function and a [`DataFrame.to_parquet`](http://pandas.pydata.org/pandas-docs/version/0.21/generated/pandas.DataFrame.to_parquet.html#pandas.DataFrame.to_parquet) method, see [here](http://pandas.pydata.org/pandas-docs/version/0.21/io.html#io-parquet).

- New user-facing dtype [`pandas.api.types.CategoricalDtype`](http://pandas.pydata.org/pandas-docs/version/0.21/generated/pandas.api.types.CategoricalDtype.html#pandas.api.types.CategoricalDtype) for specifying categoricals independent of the data, see [here](http://pandas.pydata.org/pandas-docs/version/0.21/whatsnew.html#whatsnew-0210-enhancements-categorical-dtype).

- The behavior of sum and prod on all-NaN Series/DataFrames is now consistent and no longer depends on whether [bottleneck](http://berkeleyanalytics.com/bottleneck) is installed, see [here](http://pandas.pydata.org/pandas-docs/version/0.21/whatsnew.html#whatsnew-0210-api-breaking-bottleneck).

- Compatibility fixes for pypy, see [here](http://pandas.pydata.org/pandas-docs/version/0.21/whatsnew.html#whatsnew-0210-pypy).

- Additions to the drop, reindex, and rename API to make them more consistent, see [here](http://pandas.pydata.org/pandas-docs/version/0.21/whatsnew.html#whatsnew-0210-enhancements-drop-api)

- Addition of the new methods DataFrame.infer_objects (see [here](http://pandas.pydata.org/pandas-docs/version/0.21/whatsnew.html#whatsnew-0210-enhancements-infer-objects)) and GroupBy.pipe (see [here](http://pandas.pydata.org/pandas-docs/version/0.21/whatsnew.html#whatsnew-0210-enhancements-groupby-pipe)).

- 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](http://pandas.pydata.org/pandas-docs/version/0.21/whatsnew.html#whatsnew-0210-api-breaking-loc).


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
```
v0.21.0rc1: tag_name: v0.21.0rc1
body: 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](https://parquet.apache.org/),
    including a new top-level `read_parquet` function and
    `DataFrame.to_parquet` method, see [here](https://pandas.pydata.org/pandas-docs/stable/io.html#io-parquet)
-   New user-facing `pandas.api.types.CategoricalDtype` for specifying
    categoricals independent of the data, see
    [here](https://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0210-enhancements-categorical-dtype)
-   The behavior of `sum` and `prod` on all-NaN Series/DataFrames is now
    consistent and no longer depends on whether
    [bottleneck](http://berkeleyanalytics.com/bottleneck) is installed,
    see [here](https://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0210-api-breaking-bottleneck)
-   Compatibility fixes for pypy, see [here](https://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0210-pypy)

Check the API Changes [whatsnew](https://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0210-api-breaking); and [deprecations](https://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0210-deprecations); before updating.

v0.20.3 Final: tag_name: v0.20.3
body: 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](http://pandas.pydata.org/pandas-docs/version/0.20.3/whatsnew.html) for an overview of all the bugs that have been fixed in 0.20.3.
v0.20.2 Final: tag_name: v0.20.2
body: 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](http://pandas.pydata.org/pandas-docs/version/0.20/whatsnew.html) for an overview of all the bugs that have been fixed in 0.20.2.
v0.20.1 Final: tag_name: v0.20.1
body: 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](https://github.com/pandas-dev/pandas/pull/16250).

See the [Whatsnew](http://pandas.pydata.org/pandas-docs/version/0.20/whatsnew.html) file for more information. Please report any issues [here](https://github.com/pydata/pandas/issues/).

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: tag_name: v0.20.0
body: 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](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-enhancements-agg)
- Integration with the ``feather-format``, including a new top-level ``pd.read_feather()`` and ``DataFrame.to_feather()`` method, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/io.html#io-feather)
- The ``.ix`` indexer has been deprecated, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-api-breaking-deprecate-ix)
- ``Panel`` has been deprecated, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-api-breaking-deprecate-panel)
- Addition of an ``IntervalIndex`` and ``Interval`` scalar type, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-enhancements-intervalindex)
- Improved user API when accessing levels in ``.groupby()``, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-enhancements-groupby-access)
- Improved support for ``UInt64`` dtypes, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-enhancements-uint64-support)
- A new orient for JSON serialization, ``orient='table'``, that uses the Table Schema spec, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-enhancements-table-schema)
- Experimental support for exporting ``DataFrame.style`` formats to Excel, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-enhancements-style-excel)
- Window Binary Corr/Cov operations now return a MultiIndexed ``DataFrame`` rather than a ``Panel``, as ``Panel`` is now deprecated, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-api-breaking-rolling-pairwise)
- Support for S3 handling now uses ``s3fs``, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-api-breaking-s3)
- Google BigQuery support now uses the ``pandas-gbq`` library, see [here](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html#whatsnew-0200-api-breaking-gbq)
- Switched the test framework to use [pytest](http://docs.pytest.org/)

See the [Whatsnew](http://pandas.pydata.org/pandas-docs/version/0.20.0/whatsnew.html) file for more information.
v0.20.0rc2: tag_name: v0.20.0rc2
body: **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](https://github.com/pandas-dev/pandas/issues/). 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](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-agg)
- Integration with the ``feather-format``, including a new top-level ``pd.read_feather()`` and ``DataFrame.to_feather()`` method, see [here](http://pandas-docs.github.io/pandas-docs-travis/io.html#io-feather)
- The ``.ix`` indexer has been deprecated, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-deprecate-ix)
- ``Panel`` has been deprecated, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-deprecate-panel)
- Addition of an ``IntervalIndex`` and ``Interval`` scalar type, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-intervalindex)
- Improved user API when accessing levels in ``.groupby()``, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-groupby-access)
- Improved support for ``UInt64`` dtypes, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-uint64-support)
- A new orient for JSON serialization, ``orient='table'``, that uses the Table Schema spec, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-table-schema)
- Experimental support for exporting ``DataFrame.style`` formats to Excel, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-style-excel)
- Window Binary Corr/Cov operations now return a MultiIndexed ``DataFrame`` rather than a ``Panel``, as ``Panel`` is now deprecated, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-rolling-pairwise)
- Support for S3 handling now uses ``s3fs``, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-s3)
- Google BigQuery support now uses the ``pandas-gbq`` library, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-gbq)
- Switched the test framework to use pytest

See the [Whatsnew](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html) file for more information. Please report any issues [here](https://github.com/pydata/pandas/issues/).

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: tag_name: v0.20.0rc1
body: **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](https://github.com/pandas-dev/pandas/issues/). 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](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-agg)
- Integration with the ``feather-format``, including a new top-level ``pd.read_feather()`` and ``DataFrame.to_feather()`` method, see [here](http://pandas-docs.github.io/pandas-docs-travis/io.html#io-feather)
- The ``.ix`` indexer has been deprecated, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-deprecate-ix)
- ``Panel`` has been deprecated, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-deprecate-panel)
- Addition of an ``IntervalIndex`` and ``Interval`` scalar type, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-intervalindex)
- Improved user API when accessing levels in ``.groupby()``, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-groupby-access)
- Improved support for ``UInt64`` dtypes, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-uint64-support)
- A new orient for JSON serialization, ``orient='table'``, that uses the Table Schema spec, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-table-schema)
- Experimental support for exporting ``DataFrame.style`` formats to Excel, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-enhancements-style-excel)
- Window Binary Corr/Cov operations now return a MultiIndexed ``DataFrame`` rather than a ``Panel``, as ``Panel`` is now deprecated, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-rolling-pairwise)
- Support for S3 handling now uses ``s3fs``, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-s3)
- Google BigQuery support now uses the ``pandas-gbq`` library, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0200-api-breaking-gbq)
- Switched the test framework to use pytest

See the [Whatsnew](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html) file for more information. Please report any issues [here](https://github.com/pydata/pandas/issues/).

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: tag_name: v0.19.2
body: 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](https://github.com/pandas-dev/pandas/tree/master/doc/cheatsheet/Pandas_Cheat_Sheet.pdf)

See the [v0.19.2 Whatsnew](http://pandas.pydata.org/pandas-docs/version/0.19.2/whatsnew.html) page for an overview of all bugs that have been fixed in 0.19.2.

v0.19.1 Final: tag_name: v0.19.1
body: 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](http://pandas.pydata.org/pandas-docs/version/0.19.1/whatsnew.html) for an overview of all bugs that have been fixed in 0.19.1.

v0.19.0 Final: tag_name: v0.19.0
body: 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](http://pandas.pydata.org/pandas-docs/version/0.19.0/whatsnew.html#whatsnew-0190-enhancements-asof-merge)
- `.rolling()` is now time-series aware, see [here](http://pandas.pydata.org/pandas-docs/version/0.19.0/whatsnew.html#whatsnew-0190-enhancements-rolling-ts)
- `read_csv` now supports parsing `Categorical` data, see [here](http://pandas.pydata.org/pandas-docs/version/0.19.0/whatsnew.html#whatsnew-0190-enhancements-read-csv-categorical)
- A function `union_categorical` has been added for combining categoricals, see [here](http://pandas.pydata.org/pandas-docs/version/0.19.0/whatsnew.html#whatsnew-0190-enhancements-union-categoricals)
- `PeriodIndex` now has its own `period` dtype, and changed to be more consistent with other `Index` classes. See [here](http://pandas.pydata.org/pandas-docs/version/0.19.0/whatsnew.html#whatsnew-0190-api-period)
- Sparse data structures gained enhanced support of `int` and `bool` dtypes, see [here](http://pandas.pydata.org/pandas-docs/version/0.19.0/whatsnew.html#whatsnew-0190-sparse)
- Comparison operations with `Series` no longer ignores the index, see [here](http://pandas.pydata.org/pandas-docs/version/0.19.0/whatsnew.html#whatsnew-0190-api-series-ops) for an overview of the API changes.
- Introduction of a pandas development API for utility functions, see [here](http://pandas.pydata.org/pandas-docs/version/0.19.0/whatsnew.html#whatsnew-0190-dev-api).
- Deprecation of `Panel4D` and `PanelND`. We recommend to represent these types of n-dimensional data with the [xarray package](http://xarray.pydata.org/en/stable/).
- Removal of the previously deprecated modules `pandas.io.data`, `pandas.io.wb`, `pandas.tools.rplot`.

See the [Whatsnew](http://pandas.pydata.org/pandas-docs/version/0.19.0/whatsnew.html) file for more information.

v0.19.0rc1: tag_name: v0.19.0rc1
body: **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](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0190-enhancements-asof-merge)
- `.rolling()` is now time-series aware, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0190-enhancements-rolling-ts)
- `read_csv` now supports parsing `Categorical` data, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0190-enhancements-read-csv-categorical)
- A function `union_categorical` has been added for combining categoricals, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0190-enhancements-union-categoricals)
- `PeriodIndex` now has its own `period` dtype, and changed to be more consistent with other `Index` classes. See [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0190-api-period)
- Sparse data structures gained enhanced support of `int` and `bool` dtypes, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0190-sparse)
- Comparison operations with `Series` no longer ignores the index, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0190-api-series-ops) for an overview of the API changes.
- Introduction of a pandas development API for utility functions, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0190-dev-api).
- Deprecation of `Panel4D` and `PanelND`. We recommend to represent these types of n-dimensional data with the [xarray package](http://xarray.pydata.org/en/stable/).
- Removal of the previously deprecated modules `pandas.io.data`, `pandas.io.wb`, `pandas.tools.rplot`.

See the [Whatsnew](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html) file for more information. Please report any issues [here](https://github.com/pydata/pandas/issues/).

The release candidate can be installed with [conda](http://pandas-docs.github.io/pandas-docs-travis/install.html#installing-pandas-with-anaconda) 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: tag_name: v0.18.1
body: 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](http://pandas.pydata.org/pandas-docs/version/0.18.1/whatsnew.html#whatsnew-0181-deferred-ops)
- `pd.to_datetime()` has gained the ability to assemble dates from a `DataFrame`, see [here](http://pandas.pydata.org/pandas-docs/version/0.18.1/whatsnew.html#whatsnew-0181-enhancements-assembling)
- Method chaining improvements, see [here](http://pandas.pydata.org/pandas-docs/version/0.18.1/whatsnew.html#whatsnew-0181-enhancements-method-chain)
- Custom business hour offset, see [here](http://pandas.pydata.org/pandas-docs/version/0.18.1/whatsnew.html#whatsnew-0181-enhancements-custombusinesshour)
- Many bug fixes in the handling of `sparse`, see [here](http://pandas.pydata.org/pandas-docs/version/0.18.1/whatsnew.html#whatsnew-0181-sparse)
- Expanded the [Tutorials section](http://pandas.pydata.org/pandas-docs/version/0.18.1/tutorials.html#tutorial-modern) with a feature on modern pandas, courtesy of [@TomAugsburger](https://twitter.com/TomAugspurger) (:issue:`13045`).

You an install the latest version of pandas via conda:

`conda install pandas -c conda-forge`

v0.18.0 Final: tag_name: v0.18.0
body: 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](https://github.com/pydata/pandas/issues/11273) and 3.3 [GH7718](https://github.com/pydata/pandas/issues/7718)
- Moving and expanding window functions are now methods on Series and DataFrame, similar to `.groupby`, see [here](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html#whatsnew-0180-enhancements-moments).
- Adding support for a `RangeIndex` as a specialized form of the `Int64Index`
  for memory savings, see [here](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html#whatsnew-0180-enhancements-rangeindex).
- API breaking `.resample` changes to make it more `.groupby` like, see [here](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html#whatsnew-0180-breaking-resample)
- Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a `TypeError`, see [here](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html#whatsnew-0180-float-indexers)
- The `.to_xarray()` function has been added for compatibility with the [xarray package](http://xarray.pydata.org/en/stable/) see [here](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html#whatsnew-0180-enhancements-xarray).
- The `read_sas()` function has been enhanced to read `sas7bdat` files, see [here](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html#whatsnew-0180-enhancements-sas)
- Addition of the [.str.extractall() method](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html#whatsnew-0180-enhancements-extractall), and API changes to the the [.str.extract() method](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html#whatsnew-0180-enhancements-extract), and the[.str.cat() method](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html#whatsnew-0180-enhancements-strcat)
- `pd.test()` top-level nose test runner is available [GH4327](https://github.com/pydata/pandas/issues/4327)

See the [Whatsnew](http://pandas.pydata.org/pandas-docs/version/0.18.0/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues/)

best way to get this is to install via [conda](http://http://pandas.pydata.org/pandas-docs/version/0.18.0/install.html#installing-pandas-with-anaconda). 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: tag_name: v0.18.0rc2
body: **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](https://github.com/pydata/pandas/issues/11273) and 3.3 [GH7718](https://github.com/pydata/pandas/issues/7718)
- Moving and expanding window functions are now methods on Series and DataFrame, similar to `.groupby`, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-moments).
- Adding support for a `RangeIndex` as a specialized form of the `Int64Index`
  for memory savings, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-rangeindex).
- API breaking `.resample` changes to make it more `.groupby` like, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-breaking-resample)
- Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a `TypeError`, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-float-indexers)
- The `.to_xarray()` function has been added for compatibility with the [xarray package](http://xarray.pydata.org/en/stable/) see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-xarray).
- The `read_sas()` function has been enhanced to read `sas7bdat` files, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-sas)
- Addition of the [.str.extractall() method](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-extractall), and API changes to the the [.str.extract() method](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-extract), and the[.str.cat() method](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-strcat)
- `pd.test()` top-level nose test runner is available [GH4327](https://github.com/pydata/pandas/issues/4327)

See the [Whatsnew](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues/)

best way to get this is to install via [conda](http://pandas-docs.github.io/pandas-docs-travis/install.html#installing-pandas-with-anaconda) 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: tag_name: v0.18.0rc1
body: 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](https://github.com/pydata/pandas/issues/11273) and 3.3 [GH7718](https://github.com/pydata/pandas/issues/7718)
- Moving and expanding window functions are now methods on Series and DataFrame, similar to `.groupby`, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-moments).
- Adding support for a `RangeIndex` as a specialized form of the `Int64Index`
  for memory savings, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-rangeindex).
- API breaking `.resample` changes to make it more `.groupby` like, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-breaking-resample)
- Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a `TypeError`, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-float-indexers)
- The `.to_xarray()` function has been added for compatibility with the [xarray package](http://xarray.pydata.org/en/stable/) see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-xarray).
- Addition of the [.str.extractall() method](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-extractall), and API changes to the the [.str.extract() method](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-extract), and the[.str.cat() method](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0180-enhancements-strcat)
- `pd.test()` top-level nose test runner is available [GH4327](https://github.com/pydata/pandas/issues/4327)

See the [Whatsnew](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues/)

best way to get this is to install via [conda](http://pandas-docs.github.io/pandas-docs-travis/install.html#installing-pandas-with-anaconda) 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: tag_name: v0.17.1
body: We are proud to announce that _pandas_ has become a sponsored project of the [NUMFocus organization](http://numfocus.org/news/2015/10/09/numfocus-announces-new-fiscally-sponsored-project-pandas/)
 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](http://pandas.pydata.org/pandas-docs/version/0.17.1/whatsnew.html#whatsnew-style)
- Releasing the GIL on the csv reader & other ops, see [here](http://pandas.pydata.org/pandas-docs/version/0.17.1/whatsnew.html#whatsnew-performance)
- Fixed regression in `DataFrame.drop_duplicates` from 0.16.2, causing incorrect results on integer values see [here](https://github.com/pydata/pandas/issues/11376)

See the [Whatsnew](http://pandas.pydata.org/pandas-docs/version/0.17.1/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues)

You an install the latest version of pandas via `conda`:

`conda install pandas -u pandas`

v0.17.0 Final: tag_name: v0.17.0
body: 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](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-gil)
- Plotting methods are now available as attributes of the .plot accessor, see [here](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-plot)
- The sorting API has been revamped to remove some long-time inconsistencies, see [here](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-api-breaking-sorting)
- Support for a `datetime64[ns]` with timezones as a first-class dtype, see [here](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-tz)
- The default for `to_datetime` will now be to raise when presented with unparseable formats, previously this would return the original input, see [here](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-api-breaking-to-datetime)
- The default for `dropna` in `HDFStore` has changed to `False`, to store by default all rows even if they are all NaN, see [here](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-api-breaking-hdf-dropna)
- 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](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-strftime)
- Period and PeriodIndex can handle multiplied freq like 3D, which corresponding to 3 days span. See [here](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-periodfreq)
- Development installed versions of pandas will now have PEP440 compliant version strings [GH9518](https://github.com/pydata/pandas/issues/9518)
- Development support for benchmarking with the Air Speed Velocity library [GH8361](https://github.com/pydata/pandas/pull/8361)
- Support for reading SAS xport files, see [here](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-enhancements-sas-xport)
- Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see [here](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-prior-deprecations)
- Display format with plain text can optionally align with Unicode East Asian Width, see [here](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-east-asian-width)
- Compatibility with Python 3.5 [GH11097](https://github.com/pydata/pandas/issues/11097)
- Compatibility with matplotlib 1.5.0 [GH11111](https://github.com/pydata/pandas/issues/11111)

See the [Whatsnew](http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues/10848)

You an install the latest version of pandas via `conda`:

`conda install pandas -u pandas`

v0.17.0rc2: tag_name: v0.17.0rc2
body: **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](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-gil)
- Plotting methods are now available as attributes of the .plot accessor, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-plot)
- The sorting API has been revamped to remove some long-time inconsistencies, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-api-breaking-sorting)
- Support for a `datetime64[ns]` with timezones as a first-class dtype, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-tz)
- The default for `to_datetime` will now be to raise when presented with unparseable formats, previously this would return the original input, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-api-breaking-to-datetime)
- The default for `dropna` in `HDFStore` has changed to `False`, to store by default all rows even if they are all NaN, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-api-breaking-hdf-dropna)
- 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](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-strftime)
- Period and PeriodIndex can handle multiplied freq like 3D, which corresponding to 3 days span. See [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-periodfreq)
- Development installed versions of pandas will now have PEP440 compliant version strings [GH9518](https://github.com/pydata/pandas/issues/9518)
- Development support for benchmarking with the Air Speed Velocity library [GH8361](https://github.com/pydata/pandas/pull/8361)
- Support for reading SAS xport files, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-enhancements-sas-xport)
- Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-prior-deprecations)
- Display format with plain text can optionally align with Unicode East Asian Width, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-east-asian-width)
- Compatibility with Python 3.5 [GH11097](https://github.com/pydata/pandas/issues/11097)
- Compatibility with matplotlib 1.5.0 [GH11111](https://github.com/pydata/pandas/issues/11111)

See the [Whatsnew](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues/10848)

best way to get this is to install via [conda](http://pandas-docs.github.io/pandas-docs-travis/install.html#installing-pandas-with-anaconda) 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: tag_name: v0.17.0rc1
body: **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](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-gil)
- Plotting methods are now available as attributes of the .plot accessor, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-plot)
- The sorting API has been revamped to remove some long-time inconsistencies, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-api-breaking-sorting)
- Support for a `datetime64[ns]` with timezones as a first-class dtype, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-tz)
- The default for `to_datetime` will now be to raise when presented with unparseable formats, previously this would return the original input, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-api-breaking-to-datetime)
- The default for `dropna` in `HDFStore` has changed to `False`, to store by default all rows even if they are all NaN, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-api-breaking-hdf-dropna)
- 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](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-strftime)
- Period and PeriodIndex can handle multiplied freq like 3D, which corresponding to 3 days span. See [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-periodfreq)
- Development installed versions of pandas will now have PEP440 compliant version strings [GH9518](https://github.com/pydata/pandas/issues/9518)
- Development support for benchmarking with the Air Speed Velocity library [GH8361](https://github.com/pydata/pandas/pull/8361)
- Support for reading SAS xport files, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-enhancements-sas-xport)
- Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see [here](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-prior-deprecations)

See the [Whatsnew](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues/10848)

best way to get this is to install via [conda](http://pandas-docs.github.io/pandas-docs-travis/install.html#installing-pandas-with-anaconda) 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: tag_name: v0.16.2
body: 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](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0162-enhancements-pipe)
- Documentation on how to use [numba](http://numba.pydata.org) with _pandas_, see [here](http://pandas.pydata.org/pandas-docs/stable/enhancingperf.html#enhancingperf-numba)

See the full [whatsnew](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html)

v0.16.1 Final: tag_name: v0.16.1
body: 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](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0161-enhancements-categoricalindex)
- New section on how-to-contribute to _pandas_, see [here](http://pandas.pydata.org/pandas-docs/stable/contributing.html)
- Revised "Merge, join, and concatenate" documentation, including graphical examples to make it easier to understand each operations, see [here](http://pandas.pydata.org/pandas-docs/stable/merging.html)
- New method `sample` for drawing random samples from Series, DataFrames and Panels. See [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0161-enhancements-sample)
- The default `Index` printing has changed to a more uniform format, see [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0161-index-repr)
- `BusinessHour` datetime-offset is now supported, see [here](http://pandas.pydata.org/pandas-docs/stable/timeseries.html#business-hour)
-  Further enhancement to the `.str` accessor to make string operations easier, see [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0161-enhancements-string)

See the full whatsnew [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-16-1-may-11-2015)

v0.16.0 Final: tag_name: v0.16.0
body: 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](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-enhancements-assign)
- `Series.to_coo/from_coo` methods to interact with `scipy.sparse`, see [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-enhancements-sparse)
- Backwards incompatible change to `Timedelta` to conform the `.seconds` attribute with `datetime.timedelta`, see [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-api-breaking-timedelta)
- Changes to the `.loc` slicing API to conform with the behavior of `.ix` see [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-api-breaking-indexing)
- Changes to the default for ordering in the `Categorical` constructor, see [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-api-breaking-categorical)
-  Enhancement to the `.str` accessor to make string operations easier, see [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-enhancements-string)
- The `pandas.tools.rplot`, `pandas.sandbox.qtpandas` and `pandas.rpy`
  modules are deprecated. We refer users to external packages like
  [seaborn](http://stanford.edu/~mwaskom/software/seaborn),
  [pandas-qt](https://github.com/datalyze-solutions/pandas-qt) and
  [rpy2](http://rpy.sourceforge.net/) for similar or equivalent
  functionality, see [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#deprecations) for more detail.

See the [Whatsnew](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html) for an extensive list of all API changes, enhancements and bugs that have been fixed in 0.16.0.

v0.16.0rc1: tag_name: v0.16.0rc1
body: The release candidate for 0.16.0 is now previewing.

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
- `Series.to_coo/from_coo` methods to interact with `scipy.sparse`
- Backwards incompatible change to `Timedelta` to conform the .seconds attribute with `datetime.timedelta`
- Changes to the `.loc` slicing API to conform with the behavior of `.ix`
- Changes to the default for ordering in the `Categorical` constructor

See the [Whatsnew](http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues)

v0.15.2 final: tag_name: v0.15.2
body: 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](http://pandas.pydata.org/pandas-docs/version/0.15.2/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues)

v0.15.2pre: tag_name: v0.15.2pre
body: windows builds for 0.15.2 pre-release

v0.15.1 final: tag_name: v0.15.1
body: 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](http://pandas.pydata.org/pandas-docs/version/0.15.1/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues)

v0.15.0 final: tag_name: v0.15.0
body: 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](http://pandas.pydata.org/pandas-docs/version/0.15.0/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues)

V0.15.0 RC1: tag_name: v0.15.0rc1
body: The release candidate for 0.15.0 is now previewing.

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](http://pandas.pydata.org/pandas-docs/version/0.15.0/whatsnew.html) for much more information. Please report any issues [here](https://github.com/pydata/pandas/issues)

v0.15.0 Pre-release: tag_name: v0.15pre
body: This hosts windows binaries for the v0.15.0 pre-release.

These are built with numpy 1.7 or greater.

v0.14.1 final: tag_name: v0.14.1
body: 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.

v0.14.0 final: tag_name: v0.14.0
body: 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

Pandas v0.14rc1: tag_name: v0.14.0rc1
body: Release Candiate 1

Pandas v0.13.1: tag_name: v0.13.1
Pandas v0.13.0: tag_name: v0.13.0
body: Includes hotfix for 0.13.0, with setup.py changes from #5844.
Fixing an installation error for users who do not have cython installed.