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Merge remote-tracking branch 'upstream/master' into pandas-devgh-27081 
2 parents 365362a + 911e19b commit aae2f94

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‎ci/deps/azure-36-minimum_versions.yaml

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name: pandas-dev
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channels:
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- defaults
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- conda-forge
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dependencies:
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- python=3.6.1
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- jinja2=2.8
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- numba=0.46.0
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- numexpr=2.6.2
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- numpy=1.13.3
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- numpy=1.15.4
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- openpyxl=2.5.7
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- pytables=3.4.3
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- python-dateutil=2.7.3
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- pytz=2017.2
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- scipy=0.19.0
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- scipy=1.2
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- xlrd=1.1.0
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- xlsxwriter=0.9.8
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- xlwt=1.2.0

‎ci/deps/azure-macos-36.yaml

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@@ -19,7 +19,7 @@ dependencies:
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- matplotlib=2.2.3
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- nomkl
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- numexpr
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- numpy=1.14
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- numpy=1.15.4
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- openpyxl
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- pyarrow>=0.13.0
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- pytables

‎conda.recipe/meta.yaml

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@@ -20,12 +20,12 @@ requirements:
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- cython
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- numpy
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- setuptools >=3.3
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- python-dateutil >=2.5.0
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- python-dateutil >=2.7.3
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- pytz
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run:
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- python {{ python }}
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- {{ pin_compatible('numpy') }}
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- python-dateutil >=2.5.0
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- python-dateutil >=2.7.3
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- pytz
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test:

‎doc/source/getting_started/install.rst

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@@ -220,7 +220,7 @@ Dependencies
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Package Minimum supported version
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================================================================ ==========================
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`setuptools <https://setuptools.readthedocs.io/en/latest/>`__ 24.2.0
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`NumPy <https://www.numpy.org>`__ 1.13.3
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`NumPy <https://www.numpy.org>`__ 1.15.4
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`python-dateutil <https://dateutil.readthedocs.io/en/stable/>`__ 2.7.3
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`pytz <https://pypi.org/project/pytz/>`__ 2017.2
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================================================================ ==========================

‎doc/source/whatsnew/v1.1.0.rst

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@@ -157,13 +157,23 @@ Other enhancements
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Increased minimum versions for dependencies
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Some minimum supported versions of dependencies were updated (:issue:`29766`, :issue:`29723`, pytables >= 3.4.3).
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Some minimum supported versions of dependencies were updated (:issue:`33718`, :issue:`29766`, :issue:`29723`, pytables >= 3.4.3).
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If installed, we now require:
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+-----------------+-----------------+----------+---------+
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| Package | Minimum Version | Required | Changed |
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+=================+=================+==========+=========+
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| python-dateutil | 2.7.3 | X | |
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| numpy | 1.15.4 | X | X |
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+-----------------+-----------------+----------+---------+
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| pytz | 2015.4 | X | |
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+-----------------+-----------------+----------+---------+
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| python-dateutil | 2.7.3 | X | X |
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+-----------------+-----------------+----------+---------+
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| bottleneck | 1.2.1 | | |
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+-----------------+-----------------+----------+---------+
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| numexpr | 2.6.2 | | |
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+-----------------+-----------------+----------+---------+
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| pytest (dev) | 4.0.2 | | |
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+-----------------+-----------------+----------+---------+
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For `optional libraries <https://dev.pandas.io/docs/install.html#dependencies>`_ the general recommendation is to use the latest version.
@@ -195,7 +205,7 @@ Optional libraries below the lowest tested version may still work, but are not c
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+-----------------+-----------------+---------+
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| s3fs | 0.3.0 | |
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+-----------------+-----------------+---------+
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| scipy | 0.19.0 | |
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| scipy | 1.2.0 | X |
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+-----------------+-----------------+---------+
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| sqlalchemy | 1.1.4 | |
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+-----------------+-----------------+---------+
@@ -487,6 +497,7 @@ Deprecations
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arguments (:issue:`27573`).
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- :func:`pandas.api.types.is_categorical` is deprecated and will be removed in a future version; use `:func:pandas.api.types.is_categorical_dtype` instead (:issue:`33385`)
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- :meth:`Index.get_value` is deprecated and will be removed in a future version (:issue:`19728`)
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.. ---------------------------------------------------------------------------
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@@ -546,6 +557,7 @@ Datetimelike
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- Bug in :meth:`DatetimeIndex.intersection` losing ``freq`` and timezone in some cases (:issue:`33604`)
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- Bug in :class:`DatetimeIndex` addition and subtraction with some types of :class:`DateOffset` objects incorrectly retaining an invalid ``freq`` attribute (:issue:`33779`)
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- Bug in :class:`DatetimeIndex` where setting the ``freq`` attribute on an index could silently change the ``freq`` attribute on another index viewing the same data (:issue:`33552`)
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- Bug in :meth:`DatetimeIndex.intersection` and :meth:`TimedeltaIndex.intersection` with results not having the correct ``name`` attribute (:issue:`33904`)
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Timedelta
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^^^^^^^^^
@@ -571,6 +583,7 @@ Numeric
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- Bug in :meth:`DataFrame.mean` with ``numeric_only=False`` and either ``datetime64`` dtype or ``PeriodDtype`` column incorrectly raising ``TypeError`` (:issue:`32426`)
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- Bug in :meth:`DataFrame.count` with ``level="foo"`` and index level ``"foo"`` containing NaNs causes segmentation fault (:issue:`21824`)
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- Bug in :meth:`DataFrame.diff` with ``axis=1`` returning incorrect results with mixed dtypes (:issue:`32995`)
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- Bug in DataFrame reductions using ``numeric_only=True`` and ExtensionArrays (:issue:`33256`).
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- Bug in :meth:`DataFrame.corr` and :meth:`DataFrame.cov` raising when handling nullable integer columns with ``pandas.NA`` (:issue:`33803`)
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- Bug in :class:`DataFrame` and :class:`Series` addition and subtraction between object-dtype objects and ``datetime64`` dtype objects (:issue:`33824`)
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@@ -723,6 +736,7 @@ Reshaping
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- Bug in :meth:`concat` where when passing a non-dict mapping as ``objs`` would raise a ``TypeError`` (:issue:`32863`)
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- :meth:`DataFrame.agg` now provides more descriptive ``SpecificationError`` message when attempting to aggregating non-existant column (:issue:`32755`)
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- Bug in :meth:`DataFrame.unstack` when MultiIndexed columns and MultiIndexed rows were used (:issue:`32624`, :issue:`24729` and :issue:`28306`)
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- Bug in :func:`concat` was not allowing for concatenation of ``DataFrame`` and ``Series`` with duplicate keys (:issue:`33654`)
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- Bug in :func:`cut` raised an error when non-unique labels (:issue:`33141`)
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ExtensionArray
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^^^^^^^^^^^^^^
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- Fixed bug where :meth:`Series.value_counts` would raise on empty input of ``Int64`` dtype (:issue:`33317`)
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-
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- Fixed bug where :meth:`Serires.value_counts` would raise on empty input of ``Int64`` dtype (:issue:`33317`)
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- Fixed bug that caused :meth:`Series.__repr__()` to crash for extension types whose elements are multidimensional arrays (:issue:`33770`).
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Other

‎environment.yml

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- jinja2 # pandas.Styler
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- matplotlib>=2.2.2 # pandas.plotting, Series.plot, DataFrame.plot
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- numexpr>=2.6.8
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- scipy>=1.1
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- scipy>=1.2
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- numba>=0.46.0
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# optional for io

‎pandas/__init__.py

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# numpy compat
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from pandas.compat.numpy import (
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_np_version_under1p14,
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_np_version_under1p15,
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_np_version_under1p16,
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_np_version_under1p17,
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_np_version_under1p18,

‎pandas/_libs/lib.pyx

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except TypeError as err:
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# Avoid raising TypeError on tzawareness mismatch
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# TODO: This try/except can be removed if/when Timestamp
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# comparisons are change dto match datetime, see GH#28507
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# comparisons are changed to match datetime, see GH#28507
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if "tz-naive and tz-aware" in str(err):
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return False
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raise
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if cnp.PyArray_IsZeroDim(val):
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# unbox 0-dim arrays, GH#690
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# TODO: is there a faster way to unbox?
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# item_from_zerodim?
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val = val.item()
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result[i] = val
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if cnp.PyArray_IsZeroDim(val):
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# unbox 0-dim arrays, GH#690
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# TODO: is there a faster way to unbox?
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# item_from_zerodim?
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val = val.item()
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result[i] = val

‎pandas/_libs/tslibs/timedeltas.pyx

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def __rmod__(self, other):
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# Naive implementation, room for optimization
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if hasattr(other, 'dtype') and other.dtype.kind == 'i':
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# TODO: Remove this check with backwards-compat shim
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# for integer / Timedelta is removed.
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raise TypeError(f'Invalid dtype {other.dtype} for __mod__')
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return self.__rdivmod__(other)[1]
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def __divmod__(self, other):
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15301526
def __rdivmod__(self, other):
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# Naive implementation, room for optimization
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if hasattr(other, 'dtype') and other.dtype.kind == 'i':
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# TODO: Remove this check with backwards-compat shim
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# for integer / Timedelta is removed.
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raise TypeError(f'Invalid dtype {other.dtype} for __mod__')
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div = other // self
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return div, other - div * self
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‎pandas/compat/_optional.py

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"pytest": "5.0.1",
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"pyxlsb": "1.0.6",
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"s3fs": "0.3.0",
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"scipy": "0.19.0",
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"scipy": "1.2.0",
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"sqlalchemy": "1.1.4",
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"tables": "3.4.3",
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"tabulate": "0.8.3",

‎pandas/compat/numpy/__init__.py

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# numpy versioning
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_np_version = np.__version__
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_nlv = LooseVersion(_np_version)
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_np_version_under1p14 = _nlv < LooseVersion("1.14")
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_np_version_under1p15 = _nlv < LooseVersion("1.15")
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_np_version_under1p16 = _nlv < LooseVersion("1.16")
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_np_version_under1p17 = _nlv < LooseVersion("1.17")
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_np_version_under1p18 = _nlv < LooseVersion("1.18")
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_is_numpy_dev = ".dev" in str(_nlv)
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if _nlv < "1.13.3":
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if _nlv < "1.15.4":
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raise ImportError(
21-
"this version of pandas is incompatible with numpy < 1.13.3\n"
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"this version of pandas is incompatible with numpy < 1.15.4\n"
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f"your numpy version is {_np_version}.\n"
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"Please upgrade numpy to >= 1.13.3 to use this pandas version"
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"Please upgrade numpy to >= 1.15.4 to use this pandas version"
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)
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__all__ = [
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"np",
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"_np_version",
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"_np_version_under1p14",
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"_np_version_under1p15",
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"_np_version_under1p16",
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"_np_version_under1p17",
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"_is_numpy_dev",

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