diff --git a/pandas-0.22.0.tar.gz b/pandas-0.22.0.tar.gz deleted file mode 100644 index 5068ad1..0000000 --- a/pandas-0.22.0.tar.gz +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:44a94091dd71f05922eec661638ec1a35f26d573c119aa2fad964f10a2880e6c -size 11297071 diff --git a/pandas-0.23.0.tar.gz b/pandas-0.23.0.tar.gz new file mode 100644 index 0000000..4a44be0 --- /dev/null +++ b/pandas-0.23.0.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:84ab1d50590cb2d9554211f164dc1b1a216bc94da2ba922aed2690c83f248fd9 +size 13092442 diff --git a/python-pandas-doc.changes b/python-pandas-doc.changes deleted file mode 100644 index 1f3ee11..0000000 --- a/python-pandas-doc.changes +++ /dev/null @@ -1,419 +0,0 @@ -------------------------------------------------------------------- -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 - diff --git a/python-pandas-doc.spec b/python-pandas-doc.spec deleted file mode 100644 index e79510a..0000000 --- a/python-pandas-doc.spec +++ /dev/null @@ -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 diff --git a/python-pandas.changes b/python-pandas.changes index 7a65f3f..a58fe86 100644 --- a/python-pandas.changes +++ b/python-pandas.changes @@ -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 diff --git a/python-pandas.spec b/python-pandas.spec index 98609ee..27bbd02 100644 --- a/python-pandas.spec +++ b/python-pandas.spec @@ -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