Skip to content

v0.17.0rc2

Pre-release
Pre-release
Compare
Choose a tag to compare
@jreback jreback released this 03 Oct 20:46
· 23082 commits to main since this release
v0.17.0rc2
071cffd

RELEASE CANDIDATE 2

Since release candidate 1:

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

This is a major release from 0.16.2 and includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version.

Highlights include:

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

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

best way to get this is to install via conda from our development channel. Builds for osx-64,linux-64,win-64 for Python 2.7, Python 3.4, and Python 3.5 are all available.

conda install pandas -c pandas

Assets 12
Loading