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- """ support numpy compatiblitiy across versions """
- import re
- import numpy as np
- from distutils.version import LooseVersion
- from pandas.compat import string_types, string_and_binary_types
- # numpy versioning
- _np_version = np.__version__
- _nlv = LooseVersion(_np_version)
- _np_version_under1p13 = _nlv < LooseVersion('1.13')
- _np_version_under1p14 = _nlv < LooseVersion('1.14')
- _np_version_under1p15 = _nlv < LooseVersion('1.15')
- _np_version_under1p16 = _nlv < LooseVersion('1.16')
- _np_version_under1p17 = _nlv < LooseVersion('1.17')
- if _nlv < '1.12':
- raise ImportError('this version of pandas is incompatible with '
- 'numpy < 1.12.0\n'
- 'your numpy version is {0}.\n'
- 'Please upgrade numpy to >= 1.12.0 to use '
- 'this pandas version'.format(_np_version))
- _tz_regex = re.compile('[+-]0000$')
- def tz_replacer(s):
- if isinstance(s, string_types):
- if s.endswith('Z'):
- s = s[:-1]
- elif _tz_regex.search(s):
- s = s[:-5]
- return s
- def np_datetime64_compat(s, *args, **kwargs):
- """
- provide compat for construction of strings to numpy datetime64's with
- tz-changes in 1.11 that make '2015-01-01 09:00:00Z' show a deprecation
- warning, when need to pass '2015-01-01 09:00:00'
- """
- s = tz_replacer(s)
- return np.datetime64(s, *args, **kwargs)
- def np_array_datetime64_compat(arr, *args, **kwargs):
- """
- provide compat for construction of an array of strings to a
- np.array(..., dtype=np.datetime64(..))
- tz-changes in 1.11 that make '2015-01-01 09:00:00Z' show a deprecation
- warning, when need to pass '2015-01-01 09:00:00'
- """
- # is_list_like
- if (hasattr(arr, '__iter__')
- and not isinstance(arr, string_and_binary_types)):
- arr = [tz_replacer(s) for s in arr]
- else:
- arr = tz_replacer(arr)
- return np.array(arr, *args, **kwargs)
- __all__ = ['np',
- '_np_version_under1p13',
- '_np_version_under1p14',
- '_np_version_under1p15',
- '_np_version_under1p16',
- '_np_version_under1p17'
- ]
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