old_contents: #!/usr/bin/env python
  import sys
  
  from setuptools import find_packages, setup
  
  import versioneer
  
  
  DISTNAME = 'xarray'
  LICENSE = 'Apache'
  AUTHOR = 'xarray Developers'
  AUTHOR_EMAIL = 'xarray@googlegroups.com'
  URL = 'https://github.com/pydata/xarray'
  CLASSIFIERS = [
      'Development Status :: 4 - Beta',
      'License :: OSI Approved :: Apache Software License',
      'Operating System :: OS Independent',
      'Intended Audience :: Science/Research',
      'Programming Language :: Python',
      'Programming Language :: Python :: 2',
      'Programming Language :: Python :: 2.7',
      'Programming Language :: Python :: 3',
      'Programming Language :: Python :: 3.4',
      'Programming Language :: Python :: 3.5',
      'Programming Language :: Python :: 3.6',
      'Topic :: Scientific/Engineering',
  ]
  
  INSTALL_REQUIRES = ['numpy >= 1.11', 'pandas >= 0.18.0']
  TESTS_REQUIRE = ['pytest >= 2.7.1']
  if sys.version_info[0] < 3:
      TESTS_REQUIRE.append('mock')
  
  DESCRIPTION = "N-D labeled arrays and datasets in Python"
  LONG_DESCRIPTION = """
  **xarray** (formerly **xray**) is an open source project and Python package
  that aims to bring the labeled data power of pandas_ to the physical sciences,
  by providing N-dimensional variants of the core pandas data structures.
  
  Our goal is to provide a pandas-like and pandas-compatible toolkit for
  analytics on multi-dimensional arrays, rather than the tabular data for which
  pandas excels. Our approach adopts the `Common Data Model`_ for self-
  describing scientific data in widespread use in the Earth sciences:
  ``xarray.Dataset`` is an in-memory representation of a netCDF file.
  
  .. _pandas: http://pandas.pydata.org
  .. _Common Data Model: http://www.unidata.ucar.edu/software/thredds/current/netcdf-java/CDM
  .. _netCDF: http://www.unidata.ucar.edu/software/netcdf
  .. _OPeNDAP: http://www.opendap.org/
  
  Important links
  ---------------
  
  - HTML documentation: http://xarray.pydata.org
  - Issue tracker: http://github.com/pydata/xarray/issues
  - Source code: http://github.com/pydata/xarray
  - SciPy2015 talk: https://www.youtube.com/watch?v=X0pAhJgySxk
  """  # noqa
  
  
  setup(name=DISTNAME,
        version=versioneer.get_version(),
        cmdclass=versioneer.get_cmdclass(),
        license=LICENSE,
        author=AUTHOR,
        author_email=AUTHOR_EMAIL,
        classifiers=CLASSIFIERS,
        description=DESCRIPTION,
        long_description=LONG_DESCRIPTION,
        install_requires=INSTALL_REQUIRES,
        tests_require=TESTS_REQUIRE,
        url=URL,
        packages=find_packages(),
        package_data={'xarray': ['tests/data/*']})
  
new_contents: #!/usr/bin/env python
  import sys
  
  from setuptools import find_packages, setup
  
  import versioneer
  
  
  DISTNAME = 'xarray'
  LICENSE = 'Apache'
  AUTHOR = 'xarray Developers'
  AUTHOR_EMAIL = 'xarray@googlegroups.com'
  URL = 'https://github.com/pydata/xarray'
  CLASSIFIERS = [
      'Development Status :: 4 - Beta',
      'License :: OSI Approved :: Apache Software License',
      'Operating System :: OS Independent',
      'Intended Audience :: Science/Research',
      'Programming Language :: Python',
      'Programming Language :: Python :: 2',
      'Programming Language :: Python :: 2.7',
      'Programming Language :: Python :: 3',
      'Programming Language :: Python :: 3.5',
      'Programming Language :: Python :: 3.6',
      'Topic :: Scientific/Engineering',
  ]
  
  INSTALL_REQUIRES = ['numpy >= 1.12', 'pandas >= 0.19.2']
  TESTS_REQUIRE = ['pytest >= 2.7.1']
  if sys.version_info[0] < 3:
      TESTS_REQUIRE.append('mock')
  
  DESCRIPTION = "N-D labeled arrays and datasets in Python"
  LONG_DESCRIPTION = """
  **xarray** (formerly **xray**) is an open source project and Python package
  that aims to bring the labeled data power of pandas_ to the physical sciences,
  by providing N-dimensional variants of the core pandas data structures.
  
  Our goal is to provide a pandas-like and pandas-compatible toolkit for
  analytics on multi-dimensional arrays, rather than the tabular data for which
  pandas excels. Our approach adopts the `Common Data Model`_ for self-
  describing scientific data in widespread use in the Earth sciences:
  ``xarray.Dataset`` is an in-memory representation of a netCDF file.
  
  .. _pandas: http://pandas.pydata.org
  .. _Common Data Model: http://www.unidata.ucar.edu/software/thredds/current/netcdf-java/CDM
  .. _netCDF: http://www.unidata.ucar.edu/software/netcdf
  .. _OPeNDAP: http://www.opendap.org/
  
  Important links
  ---------------
  
  - HTML documentation: http://xarray.pydata.org
  - Issue tracker: http://github.com/pydata/xarray/issues
  - Source code: http://github.com/pydata/xarray
  - SciPy2015 talk: https://www.youtube.com/watch?v=X0pAhJgySxk
  """  # noqa
  
  
  setup(name=DISTNAME,
        version=versioneer.get_version(),
        cmdclass=versioneer.get_cmdclass(),
        license=LICENSE,
        author=AUTHOR,
        author_email=AUTHOR_EMAIL,
        classifiers=CLASSIFIERS,
        description=DESCRIPTION,
        long_description=LONG_DESCRIPTION,
        install_requires=INSTALL_REQUIRES,
        tests_require=TESTS_REQUIRE,
        url=URL,
        packages=find_packages(),
        package_data={'xarray': ['tests/data/*']})
  
subject: Update minimum dependencies in setup.py