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Accepting request 610084 from devel:languages:python

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- Update to 0.23.0:
  * Round-trippable JSON format with ‘table’ orient.
  * Instantiation from dicts respects order for Python 3.6+.
  * Dependent column arguments for assign.
  * Merging / sorting on a combination of columns and index levels.
  * Extending Pandas with custom types.
  * Excluding unobserved categories from groupby.
  * Changes to make output shape of DataFrame.apply consistent.

- Do not bother generating pandas doc if it is already in both
  html and pdf provided by upstream, just point to the URL

OBS-URL: https://build.opensuse.org/request/show/610084
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-pandas?expand=0&rev=10
This commit is contained in:
Dominique Leuenberger 2018-05-19 13:38:05 +00:00 committed by Git OBS Bridge
parent 4328c07ff5
commit 4d1c673719
6 changed files with 47 additions and 494 deletions
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-------------------------------------------------------------------
Thu Jan 11 11:19:29 UTC 2018 - tchvatal@suse.com
- Format with spec-cleaner
-------------------------------------------------------------------
Wed Jan 3 22:41:40 UTC 2018 - arun@gmx.de
- specfile:
* update copyright year
- update to version 0.22.0:
* Pandas 0.22.0 changes the handling of empty and all-NA sums and
products. The summary is that
+ 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.
-------------------------------------------------------------------
Sat Dec 16 23:04:54 UTC 2017 - arun@gmx.de
- update to version 0.21.1:
* Highlights include:
+ Temporarily restore matplotlib datetime plotting
functionality. This should resolve issues for users who
implicitly relied on pandas to plot datetimes with
matplotlib. See here.
+ Improvements to the Parquet IO functions introduced in
0.21.0. See here.
* Improvements to the Parquet IO functionality
+ DataFrame.to_parquet() will now write non-default indexes when
the underlying engine supports it. The indexes will be preserved
when reading back in with read_parquet() (GH18581).
+ read_parquet() now allows to specify the columns to read from a
parquet file (GH18154)
+ read_parquet() now allows to specify kwargs which are passed to
the respective engine (GH18216)
* Other Enhancements
+ Timestamp.timestamp() is now available in Python 2.7. (GH17329)
+ Grouper and TimeGrouper now have a friendly repr output
(GH18203).
* Deprecations
+ pandas.tseries.register has been renamed to
pandas.plotting.register_matplotlib_converters`() (GH18301)
* Performance Improvements
+ Improved performance of plotting large series/dataframes
(GH18236).
* Conversion
+ Bug in TimedeltaIndex subtraction could incorrectly overflow
when NaT is present (GH17791)
+ Bug in DatetimeIndex subtracting datetimelike from DatetimeIndex
could fail to overflow (GH18020)
+ Bug in IntervalIndex.copy() when copying and IntervalIndex with
non-default closed (GH18339)
+ Bug in DataFrame.to_dict() where columns of datetime that are
tz-aware were not converted to required arrays when used with
orient='records', raising"TypeError` (GH18372)
+ Bug in DateTimeIndex and date_range() where mismatching tz-aware
start and end timezones would not raise an err if end.tzinfo is
None (GH18431)
+ Bug in Series.fillna() which raised when passed a long integer
on Python 2 (GH18159).
* Indexing
+ Bug in a boolean comparison of a datetime.datetime and a
datetime64[ns] dtype Series (GH17965)
+ Bug where a MultiIndex with more than a million records was not
raising AttributeError when trying to access a missing attribute
(GH18165)
+ Bug in IntervalIndex constructor when a list of intervals is
passed with non-default closed (GH18334)
+ Bug in Index.putmask when an invalid mask passed (GH18368)
+ Bug in masked assignment of a timedelta64[ns] dtype Series,
incorrectly coerced to float (GH18493)
* I/O
+ Bug in class:~pandas.io.stata.StataReader not converting
date/time columns with display formatting addressed
(GH17990). Previously columns with display formatting were
normally left as ordinal numbers and not converted to datetime
objects.
+ Bug in read_csv() when reading a compressed UTF-16 encoded file
(GH18071)
+ Bug in read_csv() for handling null values in index columns when
specifying na_filter=False (GH5239)
+ Bug in read_csv() when reading numeric category fields with high
cardinality (GH18186)
+ Bug in DataFrame.to_csv() when the table had MultiIndex columns,
and a list of strings was passed in for header (GH5539)
+ Bug in parsing integer datetime-like columns with specified
format in read_sql (GH17855).
+ Bug in DataFrame.to_msgpack() when serializing data of the
numpy.bool_ datatype (GH18390)
+ Bug in read_json() not decoding when reading line deliminted
JSON from S3 (GH17200)
+ Bug in pandas.io.json.json_normalize() to avoid modification of
meta (GH18610)
+ Bug in to_latex() where repeated multi-index values were not
printed even though a higher level index differed from the
previous row (GH14484)
+ Bug when reading NaN-only categorical columns in HDFStore
(GH18413)
+ Bug in DataFrame.to_latex() with longtable=True where a latex
multicolumn always spanned over three columns (GH17959)
* Plotting
+ Bug in DataFrame.plot() and Series.plot() with DatetimeIndex
where a figure generated by them is not pickleable in Python 3
(GH18439)
* Groupby/Resample/Rolling
+ Bug in DataFrame.resample(...).apply(...) when there is a
callable that returns different columns (GH15169)
+ Bug in DataFrame.resample(...) when there is a time change (DST)
and resampling frequecy is 12h or higher (GH15549)
+ Bug in pd.DataFrameGroupBy.count() when counting over a
datetimelike column (GH13393)
+ Bug in rolling.var where calculation is inaccurate with a
zero-valued array (GH18430)
* Reshaping
+ Error message in pd.merge_asof() for key datatype mismatch now
includes datatype of left and right key (GH18068)
+ Bug in pd.concat when empty and non-empty DataFrames or Series
are concatenated (GH18178 GH18187)
+ Bug in DataFrame.filter(...) when unicode is passed as a
condition in Python 2 (GH13101)
+ Bug when merging empty DataFrames when np.seterr(divide='raise')
is set (GH17776)
* Numeric
+ Bug in pd.Series.rolling.skew() and rolling.kurt() with all
equal values has floating issue (GH18044)
+ Bug in TimedeltaIndex subtraction could incorrectly overflow
when NaT is present (GH17791)
+ Bug in DatetimeIndex subtracting datetimelike from DatetimeIndex
could fail to overflow (GH18020)
* Categorical
+ Bug in DataFrame.astype() where casting to ‘category’ on an
empty DataFrame causes a segmentation fault (GH18004)
+ Error messages in the testing module have been improved when
items have different CategoricalDtype (GH18069)
+ CategoricalIndex can now correctly take a
pd.api.types.CategoricalDtype as its dtype (GH18116)
+ Bug in Categorical.unique() returning read-only codes array when
all categories were NaN (GH18051)
+ Bug in DataFrame.groupby(axis=1) with a CategoricalIndex
(GH18432)
* String
+ Series.str.split() will now propogate NaN values across all
expanded columns instead of None (GH18450)
-------------------------------------------------------------------
Mon Oct 30 06:05:48 UTC 2017 - arun@gmx.de
- specfile:
* updated minimum numpy version to 1.9.0 (see setup.py)
- update to version 0.21.0:
* Highlights include:
+ Integration with Apache Parquet, including a new top-level
read_parquet() function and DataFrame.to_parquet() method, see
here.
+ New user-facing pandas.api.types.CategoricalDtype for specifying
categoricals independent of the data, see here.
+ The behavior of sum and prod on all-NaN Series/DataFrames is now
consistent and no longer depends on whether bottleneck is
installed, see here.
+ Compatibility fixes for pypy, see here.
+ Additions to the drop, reindex and rename API to make them more
consistent, see here.
+ Addition of the new methods DataFrame.infer_objects (see here)
and GroupBy.pipe (see here).
+ Indexing with a list of labels, where one or more of the labels
is missing, is deprecated and will raise a KeyError in a future
version, see here.
* full list at http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
-------------------------------------------------------------------
Sat Sep 23 21:12:48 UTC 2017 - arun@gmx.de
- update to version 0.20.3:
* bug fix release, see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-20-3-july-7-2017
for complete changelog
- changes from version 0.20.2:
* bug fix release, see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-20-2-june-4-2017
for complete changelog
-------------------------------------------------------------------
Tue May 30 17:08:33 UTC 2017 - toddrme2178@gmail.com
- Fix documentation BuildRequires.
-------------------------------------------------------------------
Thu May 18 01:07:08 UTC 2017 - toddrme2178@gmail.com
- Update to version 0.20.1
Highlights include:
* New ``.agg()`` API for Series/DataFrame similar to the
groupby-rolling-resample API's
* Integration with the ``feather-format``, including a new
top-level ``pd.read_feather()`` and ``DataFrame.to_feather()``
method
* The ``.ix`` indexer has been deprecated
* ``Panel`` has been deprecated
* Addition of an ``IntervalIndex`` and ``Interval`` scalar type
* Improved user API when grouping by index levels in ``.groupby()``
* Improved support for ``UInt64`` dtypes
* A new orient for JSON serialization, ``orient='table'``, that
uses the Table Schema spec and that gives the possibility for
a more interactive repr in the Jupyter Notebook
* Experimental support for exporting styled DataFrames
(``DataFrame.style``) to Excel
* Window binary corr/cov operations now return a MultiIndexed
``DataFrame`` rather than a ``Panel``, as ``Panel`` is now
deprecated
* Support for S3 handling now uses ``s3fs``
* Google BigQuery support now uses the ``pandas-gbq`` library
-------------------------------------------------------------------
Tue Apr 25 18:39:03 UTC 2017 - toddrme2178@gmail.com
- Implement single-spec version.
-------------------------------------------------------------------
Thu Mar 30 15:00:41 UTC 2017 - toddrme2178@gmail.com
- update to version 0.19.2:
* Enhancements
The pd.merge_asof(), added in 0.19.0, gained some improvements:
+ pd.merge_asof() gained left_index/right_index and
left_by/right_by arguments (GH14253)
+ pd.merge_asof() can take multiple columns in by parameter and
has specialized dtypes for better performace (GH13936)
* Performance Improvements
+ Performance regression with PeriodIndex (GH14822)
+ Performance regression in indexing with getitem (GH14930)
+ Improved performance of .replace() (GH12745)
+ Improved performance Series creation with a datetime index and
dictionary data (GH14894)
* Bug Fixes
+ Compat with python 3.6 for pickling of some offsets (GH14685)
+ Compat with python 3.6 for some indexing exception types
(GH14684, GH14689)
+ Compat with python 3.6 for deprecation warnings in the test
suite (GH14681)
+ Compat with python 3.6 for Timestamp pickles (GH14689)
+ Compat with dateutil==2.6.0; segfault reported in the testing
suite (GH14621)
+ Allow nanoseconds in Timestamp.replace as a kwarg (GH14621)
+ Bug in pd.read_csv in which aliasing was being done for
na_values when passed in as a dictionary (GH14203)
+ Bug in pd.read_csv in which column indices for a dict-like
na_values were not being respected (GH14203)
+ Bug in pd.read_csv where reading files fails, if the number of
headers is equal to the number of lines in the file (GH14515)
+ Bug in pd.read_csv for the Python engine in which an unhelpful
error message was being raised when multi-char delimiters were
not being respected with quotes (GH14582)
+ Fix bugs (GH14734, GH13654) in pd.read_sas and
pandas.io.sas.sas7bdat.SAS7BDATReader that caused problems when
reading a SAS file incrementally.
+ Bug in pd.read_csv for the Python engine in which an unhelpful
error message was being raised when skipfooter was not being
respected by Python’s CSV library (GH13879)
+ Bug in .fillna() in which timezone aware datetime64 values were
incorrectly rounded (GH14872)
+ Bug in .groupby(..., sort=True) of a non-lexsorted MultiIndex
when grouping with multiple levels (GH14776)
+ Bug in pd.cut with negative values and a single bin (GH14652)
+ Bug in pd.to_numeric where a 0 was not unsigned on a
downcast='unsigned' argument (GH14401)
+ Bug in plotting regular and irregular timeseries using shared
axes (sharex=True or ax.twinx()) (GH13341, GH14322).
+ Bug in not propogating exceptions in parsing invalid datetimes,
noted in python 3.6 (GH14561)
+ Bug in resampling a DatetimeIndex in local TZ, covering a DST
change, which would raise AmbiguousTimeError (GH14682)
+ Bug in indexing that transformed RecursionError into KeyError or
IndexingError (GH14554)
+ Bug in HDFStore when writing a MultiIndex when using
data_columns=True (GH14435)
+ Bug in HDFStore.append() when writing a Series and passing a
min_itemsize argument containing a value for the index (GH11412)
+ Bug when writing to a HDFStore in table format with a
min_itemsize value for the index and without asking to append
(GH10381)
+ Bug in Series.groupby.nunique() raising an IndexError for an
empty Series (GH12553)
+ Bug in DataFrame.nlargest and DataFrame.nsmallest when the index
had duplicate values (GH13412)
+ Bug in clipboard functions on linux with python2 with unicode
and separators (GH13747)
+ Bug in clipboard functions on Windows 10 and python 3 (GH14362,
GH12807)
+ Bug in .to_clipboard() and Excel compat (GH12529)
+ Bug in DataFrame.combine_first() for integer columns (GH14687).
+ Bug in pd.read_csv() in which the dtype parameter was not being
respected for empty data (GH14712)
+ Bug in pd.read_csv() in which the nrows parameter was not being
respected for large input when using the C engine for parsing
(GH7626)
+ Bug in pd.merge_asof() could not handle timezone-aware
DatetimeIndex when a tolerance was specified (GH14844)
+ Explicit check in to_stata and StataWriter for out-of-range
values when writing doubles (GH14618)
+ Bug in .plot(kind='kde') which did not drop missing values to
generate the KDE Plot, instead generating an empty
plot. (GH14821)
+ Bug in unstack() if called with a list of column(s) as an
argument, regardless of the dtypes of all columns, they get
coerced to object (GH11847)
- update to version 0.19.1:
* Performance Improvements
+ Fixed performance regression in factorization of Period data
(GH14338)
+ Fixed performance regression in Series.asof(where) when where is
a scalar (GH14461)
+ Improved performance in DataFrame.asof(where) when where is a
scalar (GH14461)
+ Improved performance in .to_json() when lines=True (GH14408)
+ Improved performance in certain types of loc indexing with a
MultiIndex (GH14551).
* Bug Fixes
+ Source installs from PyPI will now again work without cython
installed, as in previous versions (GH14204)
+ Compat with Cython 0.25 for building (GH14496)
+ Fixed regression where user-provided file handles were closed in
read_csv (c engine) (GH14418).
+ Fixed regression in DataFrame.quantile when missing values where
present in some columns (GH14357).
+ Fixed regression in Index.difference where the freq of a
DatetimeIndex was incorrectly set (GH14323)
+ Added back pandas.core.common.array_equivalent with a
deprecation warning (GH14555).
+ Bug in pd.read_csv for the C engine in which quotation marks
were improperly parsed in skipped rows (GH14459)
+ Bug in pd.read_csv for Python 2.x in which Unicode quote
characters were no longer being respected (GH14477)
+ Fixed regression in Index.append when categorical indices were
appended (GH14545).
+ Fixed regression in pd.DataFrame where constructor fails when
given dict with None value (GH14381)
+ Fixed regression in DatetimeIndex._maybe_cast_slice_bound when
index is empty (GH14354).
+ Bug in localizing an ambiguous timezone when a boolean is passed
(GH14402)
+ Bug in TimedeltaIndex addition with a Datetime-like object where
addition overflow in the negative direction was not being caught
(GH14068, GH14453)
+ Bug in string indexing against data with object Index may raise
AttributeError (GH14424)
+ Corrrecly raise ValueError on empty input to pd.eval() and
df.query() (GH13139)
+ Bug in RangeIndex.intersection when result is a empty set
(GH14364).
+ Bug in groupby-transform broadcasting that could cause incorrect
dtype coercion (GH14457)
+ Bug in Series.__setitem__ which allowed mutating read-only
arrays (GH14359).
+ Bug in DataFrame.insert where multiple calls with duplicate
columns can fail (GH14291)
+ pd.merge() will raise ValueError with non-boolean parameters in
passed boolean type arguments (GH14434)
+ Bug in Timestamp where dates very near the minimum (1677-09)
could underflow on creation (GH14415)
+ Bug in pd.concat where names of the keys were not propagated to
the resulting MultiIndex (GH14252)
+ Bug in pd.concat where axis cannot take string parameters 'rows'
or 'columns' (GH14369)
+ Bug in pd.concat with dataframes heterogeneous in length and
tuple keys (GH14438)
+ Bug in MultiIndex.set_levels where illegal level values were
still set after raising an error (GH13754)
+ Bug in DataFrame.to_json where lines=True and a value contained
a } character (GH14391)
+ Bug in df.groupby causing an AttributeError when grouping a
single index frame by a column and the index level
(:issue`14327`)
+ Bug in df.groupby where TypeError raised when
pd.Grouper(key=...) is passed in a list (GH14334)
+ Bug in pd.pivot_table may raise TypeError or ValueError when
index or columns is not scalar and values is not specified
(GH14380)
-------------------------------------------------------------------
Mon Mar 27 19:12:32 UTC 2017 - toddrme2178@gmail.com
- Fix documentation building
-------------------------------------------------------------------
Sun Oct 23 01:32:23 UTC 2016 - toddrme2178@gmail.com
- update to version 0.19.0:
(long changelog, see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-19-0-october-2-2016)
* Highlights include:
+ merge_asof() for asof-style time-series joining
+ .rolling() is now time-series aware
+ read_csv() now supports parsing Categorical data
+ A function union_categorical() has been added for combining
categoricals
+ PeriodIndex now has its own period dtype, and changed to be more
consistent with other Index classes
+ Sparse data structures gained enhanced support of int and bool
dtypes
+ Comparison operations with Series no longer ignores the index,
see here for an overview of the API changes.
+ Introduction of a pandas development API for utility functions
+ Deprecation of Panel4D and PanelND. We recommend to represent
these types of n-dimensional data with the xarray package.
+ Removal of the previously deprecated modules pandas.io.data,
pandas.io.wb, pandas.tools.rplot.
- specfile:
* require python3-Cython
* Split documentation into own subpackage to speed up build.
* Remove buildrequires for optional dependencies to speed up build.
- Remove unneeded patches:
* 0001_disable_experimental_msgpack_big_endian.patch ^
* 0001_respect_byteorder_in_statareader.patch

68
python-pandas-doc.spec
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@ -1,68 +0,0 @@
#
# spec file for package python-pandas-doc
#
# Copyright (c) 2018 SUSE LINUX GmbH, Nuernberg, Germany.
#
# All modifications and additions to the file contributed by third parties
# remain the property of their copyright owners, unless otherwise agreed
# upon. The license for this file, and modifications and additions to the
# file, is the same license as for the pristine package itself (unless the
# license for the pristine package is not an Open Source License, in which
# case the license is the MIT License). An "Open Source License" is a
# license that conforms to the Open Source Definition (Version 1.9)
# published by the Open Source Initiative.
# Please submit bugfixes or comments via http://bugs.opensuse.org/
#
%{?!python_module:%define python_module() python-%{**} python3-%{**}}
Name: python-pandas-doc
Version: 0.22.0
Release: 0
Summary: Documentation for python-pandas
License: BSD-3-Clause
Group: Documentation/HTML
Url: http://pandas.pydata.org/
Source0: https://files.pythonhosted.org/packages/source/p/pandas/pandas-%{version}.tar.gz
BuildRequires: %{python_module pandas = %{version}}
BuildRequires: gcc-c++
BuildRequires: python-rpm-macros
BuildRequires: python3-Sphinx
BuildRequires: python3-devel
BuildRequires: python3-jupyter_client
BuildRequires: python3-jupyter_ipykernel
BuildRequires: python3-jupyter_nbconvert
BuildRequires: python3-jupyter_nbformat
BuildRequires: python3-jupyter_nbsphinx
BuildRequires: python3-matplotlib
BuildRequires: python3-numpy-devel >= 1.7.1
BuildRequires: python3-python-dateutil >= 1.5
BuildRequires: python3-pytz
BuildRequires: python3-scipy
BuildRequires: python3-setuptools
Provides: %{python_module pandas-doc = %{version}}
BuildArch: noarch
%description
Documentation, help files, and examples for python3-pandas.
%prep
%setup -q -n pandas-%{version}
%build
python3 setup.py build_ext --inplace
pushd doc
python3 make.py html
popd
%install
mkdir -p %{buildroot}%{_docdir}/python-pandas
cp -r doc/build/html %{buildroot}%{_docdir}/python-pandas/
%files
%doc LICENSE
%{_docdir}/python-pandas/
%changelog

18
python-pandas.changes
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@ -1,3 +1,21 @@
-------------------------------------------------------------------
Thu May 17 12:28:44 UTC 2018 - tchvatal@suse.com
- Update to 0.23.0:
* Round-trippable JSON format with ‘table’ orient.
* Instantiation from dicts respects order for Python 3.6+.
* Dependent column arguments for assign.
* Merging / sorting on a combination of columns and index levels.
* Extending Pandas with custom types.
* Excluding unobserved categories from groupby.
* Changes to make output shape of DataFrame.apply consistent.
-------------------------------------------------------------------
Thu May 17 12:06:17 UTC 2018 - tchvatal@suse.com
- Do not bother generating pandas doc if it is already in both
html and pdf provided by upstream, just point to the URL
-------------------------------------------------------------------
Thu Jan 11 11:18:48 UTC 2018 - tchvatal@suse.com

30
python-pandas.spec
View File

@ -17,25 +17,39 @@
%{?!python_module:%define python_module() python-%{**} python3-%{**}}
%define oldpython python
Name: python-pandas
Version: 0.22.0
Version: 0.23.0
Release: 0
Summary: Make working with "relational" or "labeled" data both easy and intuitive
License: BSD-3-Clause
Group: Development/Libraries/Python
Url: http://pandas.pydata.org/
URL: http://pandas.pydata.org/
Source0: https://files.pythonhosted.org/packages/source/p/pandas/pandas-%{version}.tar.gz
BuildRequires: %{python_module Cython}
BuildRequires: %{python_module SQLAlchemy}
BuildRequires: %{python_module XlsxWriter}
BuildRequires: %{python_module beautifulsoup4}
BuildRequires: %{python_module devel}
BuildRequires: %{python_module lxml}
BuildRequires: %{python_module nose}
BuildRequires: %{python_module numpy-devel >= 1.9.0}
BuildRequires: %{python_module pytest}
BuildRequires: %{python_module python-dateutil >= 1.5}
BuildRequires: %{python_module python-dateutil}
BuildRequires: %{python_module pytz}
BuildRequires: %{python_module setuptools}
BuildRequires: %{python_module six}
BuildRequires: %{python_module xlrd}
BuildRequires: fdupes
BuildRequires: gcc-c++
BuildRequires: python-rpm-macros
Requires: python-Cython
Requires: python-lxml
Requires: python-numpy >= 1.9.0
Requires: python-python-dateutil >= 1.5
Requires: python-pytz
Requires: python-six
Recommends: python-Bottleneck
Recommends: python-Jinja2
Recommends: python-SQLAlchemy >= 0.8.1
@ -45,7 +59,6 @@ Recommends: python-blosc
Recommends: python-boto
Recommends: python-google-api-python-client
Recommends: python-html5lib
Recommends: python-lxml
Recommends: python-matplotlib
Recommends: python-numexpr >= 2.1
Recommends: python-oauth2client
@ -59,8 +72,10 @@ Recommends: python-xarray >= 0.7.0
Recommends: python-xlrd
Recommends: python-xlwt
Recommends: xclip
Obsoletes: python-pandas-doc
%ifpython2
Recommends: python-backports.lzma
Obsoletes: %{oldpython}-pandas-doc
%endif
%python_subpackages
@ -72,6 +87,8 @@ doing practical, real world data analysis in Python. Additionally, it has
the broader goal of becoming the most powerful and flexible open source data
analysis / manipulation tool available in any language.
http://pandas.pydata.org/pandas-docs/stable/
%prep
%setup -q -n pandas-%{version}
@ -85,8 +102,13 @@ export CFLAGS="%{optflags} -fno-strict-aliasing"
%python_expand rm -r %{buildroot}%{$python_sitearch}/pandas/tests
# Needs X and various other fun to work
#%check
#%%python_expand PYTHONPATH=%{buildroot}%{$python_sitearch} py.test-%{$python_version} pandas/tests
%files %{python_files}
%doc LICENSE doc/README.rst RELEASE.md
%license LICENSE
%doc doc/README.rst RELEASE.md
%{python_sitearch}/pandas/
%{python_sitearch}/pandas-%{version}-py*.egg-info