[Numpy-discussion] ANN: pandas v0.17.0rc2

Discussion:

[Numpy-discussion] ANN: pandas v0.17.0rc2 - RELEASE CANDIDATE 2

Jeff Reback

2015-10-03 21:33:34 UTC

Hi,

I'm pleased to announce the availability of the second release candidate of
Pandas 0.17.0.
Please try this RC and report any issues here: Pandas Issues
<https://github.com/pydata/pandas/issues/10848>
We will be releasing officially on October 9.

**RELEASE CANDIDATE 2**

From RC 1 we have:

- 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>
- Support for Series.dt.strftime to generate formatted strings for
datetime-likes, see here
<http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-strftime>
- 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 GH8316 <https://github.com/pydata/pandas/pull/8316>
- 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.

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 (for osx/linux) are all available.

conda install pandas -c pandas

Thanks to all who made this release happen. It is a very large release!

Jeff

Matthew Brett

2015-10-04 05:35:42 UTC

Permalink

Hi,

Post by Jeff Reback
Hi,
I'm pleased to announce the availability of the second release candidate of
Pandas 0.17.0.
Please try this RC and report any issues here: Pandas Issues
We will be releasing officially on October 9.
**RELEASE CANDIDATE 2**
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.
Release the Global Interpreter Lock (GIL) on some cython operations, see
here
Plotting methods are now available as attributes of the .plot accessor, see
here
The sorting API has been revamped to remove some long-time inconsistencies,
see here
Support for a datetime64[ns] with timezones as a first-class dtype, see here
The default for to_datetime will now be to raise when presented with
unparseable formats, previously this would return the original input, see
here
The default for dropna in HDFStore has changed to False, to store by default
all rows even if they are all NaN, see here
Support for Series.dt.strftime to generate formatted strings for
datetime-likes, see here
Development installed versions of pandas will now have PEP440 compliant
version strings GH9518
Development support for benchmarking with the Air Speed Velocity library
GH8316
Support for reading SAS xport files, see here
Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0,
see here
Display format with plain text can optionally align with Unicode East Asian
Width, see here
Compatibility with Python 3.5 GH11097
Compatibility with matplotlib 1.5.0 GH11111
See the Whatsnew for much more information.
Best way to get this is to install via conda from our development channel.
Builds for osx-64,linux-64,win-64 for Python 2.7, Python 3.4, and Python 3.5
(for osx/linux) are all available.
conda install pandas -c pandas

I built OSX wheels for Pythons 2.7, 3.4, 3.5. To test:

pip install --pre -f http://wheels.scipy.org pandas

There were some test failures for Python 3.3 - issue here:

https://github.com/pydata/pandas/issues/11232

Cheers,

Matthew

Jeff Reback

2015-10-05 22:00:38 UTC

Permalink

it should be exactly the same
(they are going to release soon as well I think) - with an updated version

hi,
on pypi, pandas_datareader (0.1.1) is dated from April 10th.
Is it up-to-date with pandas 0.17rc2 ?

Post by Matthew Brett
Hi,

pip install --pre -f http://wheels.scipy.org pandas
https://github.com/pydata/pandas/issues/11232
Cheers,
Matthew

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