From 52e811568e6230e2414b1b53a97b7f9f790e957a Mon Sep 17 00:00:00 2001 From: Jeff Reback Date: Mon, 17 Jul 2017 20:55:56 -0400 Subject: [PATCH] DEPS: set min versions closes #15206, numpy >= 1.9 closes #15543, matplotlib >= 1.4.3 scipy >= 0.14.0 --- .travis.yml | 6 +- ci/install_travis.sh | 2 +- ci/requirements-2.7_COMPAT.build | 2 +- ci/requirements-2.7_COMPAT.run | 9 +- ci/requirements-2.7_LOCALE.build | 2 +- ci/requirements-2.7_LOCALE.run | 5 +- ci/requirements-2.7_SLOW.build | 2 +- ci/requirements-2.7_SLOW.run | 4 +- ci/script_multi.sh | 6 + ci/script_single.sh | 9 + doc/source/install.rst | 6 +- doc/source/whatsnew/v0.21.0.txt | 22 ++- pandas/_libs/sparse.pyx | 2 - pandas/compat/numpy/__init__.py | 14 +- pandas/core/algorithms.py | 7 +- pandas/core/generic.py | 5 +- pandas/core/groupby.py | 8 +- pandas/core/internals.py | 16 +- pandas/tests/frame/test_quantile.py | 42 ----- pandas/tests/frame/test_rank.py | 2 + .../tests/indexes/datetimes/test_datetime.py | 8 +- pandas/tests/indexes/period/test_indexing.py | 34 ++-- .../indexes/timedeltas/test_timedelta.py | 8 +- pandas/tests/plotting/common.py | 3 +- pandas/tests/plotting/test_datetimelike.py | 2 + pandas/tests/plotting/test_frame.py | 163 ++++++++++-------- pandas/tests/plotting/test_misc.py | 45 +---- pandas/tests/plotting/test_series.py | 12 ++ pandas/tests/series/test_operators.py | 16 +- pandas/tests/series/test_quantile.py | 27 +-- pandas/tests/series/test_rank.py | 2 + pandas/tests/sparse/test_array.py | 7 +- pandas/tests/test_nanops.py | 18 +- pandas/tests/test_resample.py | 2 +- pandas/tests/tools/test_numeric.py | 5 +- setup.py | 2 +- 36 files changed, 217 insertions(+), 308 deletions(-) diff --git a/.travis.yml b/.travis.yml index 897d31cf23a3b..034e2a32bb75c 100644 --- a/.travis.yml +++ b/.travis.yml @@ -37,7 +37,7 @@ matrix: - JOB="3.5_OSX" TEST_ARGS="--skip-slow --skip-network" - dist: trusty env: - - JOB="2.7_LOCALE" TEST_ARGS="--only-slow --skip-network" LOCALE_OVERRIDE="zh_CN.UTF-8" + - JOB="2.7_LOCALE" LOCALE_OVERRIDE="zh_CN.UTF-8" SLOW=true addons: apt: packages: @@ -62,7 +62,7 @@ matrix: # In allow_failures - dist: trusty env: - - JOB="2.7_SLOW" TEST_ARGS="--only-slow --skip-network" + - JOB="2.7_SLOW" SLOW=true # In allow_failures - dist: trusty env: @@ -82,7 +82,7 @@ matrix: allow_failures: - dist: trusty env: - - JOB="2.7_SLOW" TEST_ARGS="--only-slow --skip-network" + - JOB="2.7_SLOW" SLOW=true - dist: trusty env: - JOB="2.7_BUILD_TEST" TEST_ARGS="--skip-slow" BUILD_TEST=true diff --git a/ci/install_travis.sh b/ci/install_travis.sh index ad8f0bdd8a597..d26689f2e6b4b 100755 --- a/ci/install_travis.sh +++ b/ci/install_travis.sh @@ -47,7 +47,7 @@ which conda echo echo "[update conda]" conda config --set ssl_verify false || exit 1 -conda config --set always_yes true --set changeps1 false || exit 1 +conda config --set quiet true --set always_yes true --set changeps1 false || exit 1 conda update -q conda echo diff --git a/ci/requirements-2.7_COMPAT.build b/ci/requirements-2.7_COMPAT.build index 0e1ccf9eac9bf..d9c932daa110b 100644 --- a/ci/requirements-2.7_COMPAT.build +++ b/ci/requirements-2.7_COMPAT.build @@ -1,5 +1,5 @@ python=2.7* -numpy=1.7.1 +numpy=1.9.2 cython=0.23 dateutil=1.5 pytz=2013b diff --git a/ci/requirements-2.7_COMPAT.run b/ci/requirements-2.7_COMPAT.run index b94f4ab7b27d1..d1324ea9c8977 100644 --- a/ci/requirements-2.7_COMPAT.run +++ b/ci/requirements-2.7_COMPAT.run @@ -1,11 +1,12 @@ -numpy=1.7.1 +numpy=1.9.2 dateutil=1.5 pytz=2013b -scipy=0.11.0 +scipy=0.14.0 xlwt=0.7.5 xlrd=0.9.2 -numexpr=2.2.2 -pytables=3.0.0 +bottleneck=1.0.0 +numexpr=2.4.4 # this is actually unsupported for non-pytables +pytables=3.2.2 psycopg2 pymysql=0.6.0 sqlalchemy=0.7.8 diff --git a/ci/requirements-2.7_LOCALE.build b/ci/requirements-2.7_LOCALE.build index 4a37ce8fbe161..96cb184ec2665 100644 --- a/ci/requirements-2.7_LOCALE.build +++ b/ci/requirements-2.7_LOCALE.build @@ -1,5 +1,5 @@ python=2.7* python-dateutil pytz=2013b -numpy=1.8.2 +numpy=1.9.2 cython=0.23 diff --git a/ci/requirements-2.7_LOCALE.run b/ci/requirements-2.7_LOCALE.run index 8e360cf74b081..00006106f7009 100644 --- a/ci/requirements-2.7_LOCALE.run +++ b/ci/requirements-2.7_LOCALE.run @@ -1,11 +1,12 @@ python-dateutil pytz=2013b -numpy=1.8.2 +numpy=1.9.2 xlwt=0.7.5 openpyxl=1.6.2 xlsxwriter=0.5.2 xlrd=0.9.2 -matplotlib=1.3.1 +bottleneck=1.0.0 +matplotlib=1.4.3 sqlalchemy=0.8.1 lxml=3.2.1 scipy diff --git a/ci/requirements-2.7_SLOW.build b/ci/requirements-2.7_SLOW.build index 0f4a2c6792e6b..a665ab9edd585 100644 --- a/ci/requirements-2.7_SLOW.build +++ b/ci/requirements-2.7_SLOW.build @@ -1,5 +1,5 @@ python=2.7* python-dateutil pytz -numpy=1.8.2 +numpy=1.10* cython diff --git a/ci/requirements-2.7_SLOW.run b/ci/requirements-2.7_SLOW.run index 0a549554f5219..f7708283ad04a 100644 --- a/ci/requirements-2.7_SLOW.run +++ b/ci/requirements-2.7_SLOW.run @@ -1,7 +1,7 @@ python-dateutil pytz -numpy=1.8.2 -matplotlib=1.3.1 +numpy=1.10* +matplotlib=1.4.3 scipy patsy xlwt diff --git a/ci/script_multi.sh b/ci/script_multi.sh index d79fc43fbe175..ee9fbcaad5ef5 100755 --- a/ci/script_multi.sh +++ b/ci/script_multi.sh @@ -36,9 +36,15 @@ elif [ "$COVERAGE" ]; then echo pytest -s -n 2 -m "not single" --cov=pandas --cov-report xml:/tmp/cov-multiple.xml --junitxml=/tmp/multiple.xml $TEST_ARGS pandas pytest -s -n 2 -m "not single" --cov=pandas --cov-report xml:/tmp/cov-multiple.xml --junitxml=/tmp/multiple.xml $TEST_ARGS pandas +elif [ "$SLOW" ]; then + TEST_ARGS="--only-slow --skip-network" + echo pytest -r xX -m "not single and slow" -v --junitxml=/tmp/multiple.xml $TEST_ARGS pandas + pytest -r xX -m "not single and slow" -v --junitxml=/tmp/multiple.xml $TEST_ARGS pandas + else echo pytest -n 2 -r xX -m "not single" --junitxml=/tmp/multiple.xml $TEST_ARGS pandas pytest -n 2 -r xX -m "not single" --junitxml=/tmp/multiple.xml $TEST_ARGS pandas # TODO: doctest + fi RET="$?" diff --git a/ci/script_single.sh b/ci/script_single.sh index 245b4e6152c4d..8df9284e645ab 100755 --- a/ci/script_single.sh +++ b/ci/script_single.sh @@ -14,14 +14,23 @@ fi if [ "$BUILD_TEST" ]; then echo "We are not running pytest as this is a build test." + elif [ "$DOC" ]; then echo "We are not running pytest as this is a doc-build" + elif [ "$COVERAGE" ]; then echo pytest -s -m "single" --cov=pandas --cov-report xml:/tmp/cov-single.xml --junitxml=/tmp/single.xml $TEST_ARGS pandas pytest -s -m "single" --cov=pandas --cov-report xml:/tmp/cov-single.xml --junitxml=/tmp/single.xml $TEST_ARGS pandas + +elif [ "$SLOW" ]; then + TEST_ARGS="--only-slow --skip-network" + echo pytest -r xX -m "single and slow" -v --junitxml=/tmp/multiple.xml $TEST_ARGS pandas + pytest -r xX -m "single and slow" -v --junitxml=/tmp/multiple.xml $TEST_ARGS pandas + else echo pytest -m "single" -r xX --junitxml=/tmp/single.xml $TEST_ARGS pandas pytest -m "single" -r xX --junitxml=/tmp/single.xml $TEST_ARGS pandas # TODO: doctest + fi RET="$?" diff --git a/doc/source/install.rst b/doc/source/install.rst index 99d299b75b59b..f92c43839ee31 100644 --- a/doc/source/install.rst +++ b/doc/source/install.rst @@ -203,7 +203,7 @@ Dependencies ------------ * `setuptools `__ -* `NumPy `__: 1.7.1 or higher +* `NumPy `__: 1.9.0 or higher * `python-dateutil `__: 1.5 or higher * `pytz `__: Needed for time zone support @@ -233,7 +233,7 @@ Optional Dependencies * `Cython `__: Only necessary to build development version. Version 0.23 or higher. -* `SciPy `__: miscellaneous statistical functions +* `SciPy `__: miscellaneous statistical functions, Version 0.14.0 or higher * `xarray `__: pandas like handling for > 2 dims, needed for converting Panels to xarray objects. Version 0.7.0 or higher is recommended. * `PyTables `__: necessary for HDF5-based storage. Version 3.0.0 or higher required, Version 3.2.1 or higher highly recommended. * `Feather Format `__: necessary for feather-based storage, version 0.3.1 or higher. @@ -244,7 +244,7 @@ Optional Dependencies * `pymysql `__: for MySQL. * `SQLite `__: for SQLite, this is included in Python's standard library by default. -* `matplotlib `__: for plotting +* `matplotlib `__: for plotting, Version 1.4.3 or higher. * For Excel I/O: * `xlrd/xlwt `__: Excel reading (xlrd) and writing (xlwt) diff --git a/doc/source/whatsnew/v0.21.0.txt b/doc/source/whatsnew/v0.21.0.txt index c5fe89282bf52..72eb4d4ec7240 100644 --- a/doc/source/whatsnew/v0.21.0.txt +++ b/doc/source/whatsnew/v0.21.0.txt @@ -138,6 +138,27 @@ Other Enhancements Backwards incompatible API changes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. _whatsnew_0210.api_breaking.deps: + +Dependencies have increased minimum versions +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +We have updated our minimum supported versions of dependencies (:issue:`15206`, :issue:`15543`, :issue:`15214`) +). If installed, we now require: + + +--------------+-----------------+----------+ + | Package | Minimum Version | Required | + +======================+=========+==========+ + | Numpy | 1.9.0 | X | + +--------------+-----------------+----------+ + | Matplotlib | 1.4.3 | | + +--------------+-----------------+----------+ + | Scipy | 0.14.0 | | + +--------------+-----------------+----------+ + | Bottleneck | 1.0.0 | | + +--------------+-----------------+----------+ + .. _whatsnew_0210.api_breaking.pandas_eval: Improved error handling during item assignment in pd.eval @@ -259,7 +280,6 @@ Other API Changes ^^^^^^^^^^^^^^^^^ - Support has been dropped for Python 3.4 (:issue:`15251`) -- Support has been dropped for bottleneck < 1.0.0 (:issue:`15214`) - The Categorical constructor no longer accepts a scalar for the ``categories`` keyword. (:issue:`16022`) - Accessing a non-existent attribute on a closed :class:`~pandas.HDFStore` will now raise an ``AttributeError`` rather than a ``ClosedFileError`` (:issue:`16301`) diff --git a/pandas/_libs/sparse.pyx b/pandas/_libs/sparse.pyx index 0c2e056ead7fa..1cc7f5ace95ea 100644 --- a/pandas/_libs/sparse.pyx +++ b/pandas/_libs/sparse.pyx @@ -12,8 +12,6 @@ from distutils.version import LooseVersion # numpy versioning _np_version = np.version.short_version -_np_version_under1p8 = LooseVersion(_np_version) < '1.8' -_np_version_under1p9 = LooseVersion(_np_version) < '1.9' _np_version_under1p10 = LooseVersion(_np_version) < '1.10' _np_version_under1p11 = LooseVersion(_np_version) < '1.11' diff --git a/pandas/compat/numpy/__init__.py b/pandas/compat/numpy/__init__.py index 2c5a18973afa8..5112957b49875 100644 --- a/pandas/compat/numpy/__init__.py +++ b/pandas/compat/numpy/__init__.py @@ -9,19 +9,18 @@ # numpy versioning _np_version = np.__version__ _nlv = LooseVersion(_np_version) -_np_version_under1p8 = _nlv < '1.8' -_np_version_under1p9 = _nlv < '1.9' _np_version_under1p10 = _nlv < '1.10' _np_version_under1p11 = _nlv < '1.11' _np_version_under1p12 = _nlv < '1.12' _np_version_under1p13 = _nlv < '1.13' _np_version_under1p14 = _nlv < '1.14' +_np_version_under1p15 = _nlv < '1.15' -if _nlv < '1.7.0': +if _nlv < '1.9': raise ImportError('this version of pandas is incompatible with ' - 'numpy < 1.7.0\n' + 'numpy < 1.9.0\n' 'your numpy version is {0}.\n' - 'Please upgrade numpy to >= 1.7.0 to use ' + 'Please upgrade numpy to >= 1.9.0 to use ' 'this pandas version'.format(_np_version)) @@ -70,11 +69,10 @@ def np_array_datetime64_compat(arr, *args, **kwargs): __all__ = ['np', - '_np_version_under1p8', - '_np_version_under1p9', '_np_version_under1p10', '_np_version_under1p11', '_np_version_under1p12', '_np_version_under1p13', - '_np_version_under1p14' + '_np_version_under1p14', + '_np_version_under1p15' ] diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py index f2359f3ff1a9d..ffd03096e2a27 100644 --- a/pandas/core/algorithms.py +++ b/pandas/core/algorithms.py @@ -6,7 +6,6 @@ from warnings import warn, catch_warnings import numpy as np -from pandas import compat, _np_version_under1p8 from pandas.core.dtypes.cast import maybe_promote from pandas.core.dtypes.generic import ( ABCSeries, ABCIndex, @@ -407,14 +406,12 @@ def isin(comps, values): comps, dtype, _ = _ensure_data(comps) values, _, _ = _ensure_data(values, dtype=dtype) - # GH11232 - # work-around for numpy < 1.8 and comparisions on py3 # faster for larger cases to use np.in1d f = lambda x, y: htable.ismember_object(x, values) + # GH16012 # Ensure np.in1d doesn't get object types or it *may* throw an exception - if ((_np_version_under1p8 and compat.PY3) or len(comps) > 1000000 and - not is_object_dtype(comps)): + if len(comps) > 1000000 and not is_object_dtype(comps): f = lambda x, y: np.in1d(x, y) elif is_integer_dtype(comps): try: diff --git a/pandas/core/generic.py b/pandas/core/generic.py index c83b1073afc8e..5f0aac53d71f6 100644 --- a/pandas/core/generic.py +++ b/pandas/core/generic.py @@ -1827,11 +1827,8 @@ def _box_item_values(self, key, values): def _maybe_cache_changed(self, item, value): """The object has called back to us saying maybe it has changed. - - numpy < 1.8 has an issue with object arrays and aliasing - GH6026 """ - self._data.set(item, value, check=pd._np_version_under1p8) + self._data.set(item, value, check=False) @property def _is_cached(self): diff --git a/pandas/core/groupby.py b/pandas/core/groupby.py index a388892e925b6..aa7c4517c0a01 100644 --- a/pandas/core/groupby.py +++ b/pandas/core/groupby.py @@ -13,7 +13,7 @@ ) from pandas import compat -from pandas.compat.numpy import function as nv, _np_version_under1p8 +from pandas.compat.numpy import function as nv from pandas.compat import set_function_name from pandas.core.dtypes.common import ( @@ -3257,11 +3257,7 @@ def value_counts(self, normalize=False, sort=True, ascending=False, d = np.diff(np.r_[idx, len(ids)]) if dropna: m = ids[lab == -1] - if _np_version_under1p8: - mi, ml = algorithms.factorize(m) - d[ml] = d[ml] - np.bincount(mi) - else: - np.add.at(d, m, -1) + np.add.at(d, m, -1) acc = rep(d)[mask] else: acc = rep(d) diff --git a/pandas/core/internals.py b/pandas/core/internals.py index b616270e47aa6..83b382ec0ed72 100644 --- a/pandas/core/internals.py +++ b/pandas/core/internals.py @@ -69,8 +69,7 @@ import pandas.core.computation.expressions as expressions from pandas.util._decorators import cache_readonly from pandas.util._validators import validate_bool_kwarg - -from pandas import compat, _np_version_under1p9 +from pandas import compat from pandas.compat import range, map, zip, u @@ -857,9 +856,6 @@ def _is_empty_indexer(indexer): # set else: - if _np_version_under1p9: - # Work around GH 6168 to support old numpy - indexer = getattr(indexer, 'values', indexer) values[indexer] = value # coerce and try to infer the dtypes of the result @@ -1482,15 +1478,7 @@ def quantile(self, qs, interpolation='linear', axis=0, mgr=None): tuple of (axis, block) """ - if _np_version_under1p9: - if interpolation != 'linear': - raise ValueError("Interpolation methods other than linear " - "are not supported in numpy < 1.9.") - - kw = {} - if not _np_version_under1p9: - kw.update({'interpolation': interpolation}) - + kw = {'interpolation': interpolation} values = self.get_values() values, _, _, _ = self._try_coerce_args(values, values) diff --git a/pandas/tests/frame/test_quantile.py b/pandas/tests/frame/test_quantile.py index 2482e493dbefd..2f264874378bc 100644 --- a/pandas/tests/frame/test_quantile.py +++ b/pandas/tests/frame/test_quantile.py @@ -12,7 +12,6 @@ from pandas.util.testing import assert_series_equal, assert_frame_equal import pandas.util.testing as tm -from pandas import _np_version_under1p9 from pandas.tests.frame.common import TestData @@ -103,9 +102,6 @@ def test_quantile_axis_parameter(self): def test_quantile_interpolation(self): # see gh-10174 - if _np_version_under1p9: - pytest.skip("Numpy version under 1.9") - from numpy import percentile # interpolation = linear (default case) @@ -166,44 +162,6 @@ def test_quantile_interpolation(self): index=[.25, .5], columns=['a', 'b', 'c']) assert_frame_equal(result, expected) - def test_quantile_interpolation_np_lt_1p9(self): - # see gh-10174 - if not _np_version_under1p9: - pytest.skip("Numpy version is greater than 1.9") - - from numpy import percentile - - # interpolation = linear (default case) - q = self.tsframe.quantile(0.1, axis=0, interpolation='linear') - assert q['A'] == percentile(self.tsframe['A'], 10) - q = self.intframe.quantile(0.1) - assert q['A'] == percentile(self.intframe['A'], 10) - - # test with and without interpolation keyword - q1 = self.intframe.quantile(0.1) - assert q1['A'] == np.percentile(self.intframe['A'], 10) - assert_series_equal(q, q1) - - # interpolation method other than default linear - msg = "Interpolation methods other than linear" - df = DataFrame({"A": [1, 2, 3], "B": [2, 3, 4]}, index=[1, 2, 3]) - with tm.assert_raises_regex(ValueError, msg): - df.quantile(.5, axis=1, interpolation='nearest') - - with tm.assert_raises_regex(ValueError, msg): - df.quantile([.5, .75], axis=1, interpolation='lower') - - # test degenerate case - df = DataFrame({'x': [], 'y': []}) - with tm.assert_raises_regex(ValueError, msg): - q = df.quantile(0.1, axis=0, interpolation='higher') - - # multi - df = DataFrame([[1, 1, 1], [2, 2, 2], [3, 3, 3]], - columns=['a', 'b', 'c']) - with tm.assert_raises_regex(ValueError, msg): - df.quantile([.25, .5], interpolation='midpoint') - def test_quantile_multi(self): df = DataFrame([[1, 1, 1], [2, 2, 2], [3, 3, 3]], columns=['a', 'b', 'c']) diff --git a/pandas/tests/frame/test_rank.py b/pandas/tests/frame/test_rank.py index acf887d047c9e..78734f60e55b7 100644 --- a/pandas/tests/frame/test_rank.py +++ b/pandas/tests/frame/test_rank.py @@ -1,4 +1,5 @@ # -*- coding: utf-8 -*- +import pytest from datetime import timedelta, datetime from distutils.version import LooseVersion from numpy import nan @@ -195,6 +196,7 @@ def test_rank_axis(self): def test_rank_methods_frame(self): tm.skip_if_no_package('scipy', min_version='0.13', app='scipy.stats.rankdata') + pytest.importorskip('scipy.stats.special') import scipy from scipy.stats import rankdata diff --git a/pandas/tests/indexes/datetimes/test_datetime.py b/pandas/tests/indexes/datetimes/test_datetime.py index f99dcee9e5c8a..47f53f53cfd02 100644 --- a/pandas/tests/indexes/datetimes/test_datetime.py +++ b/pandas/tests/indexes/datetimes/test_datetime.py @@ -9,7 +9,7 @@ from pandas.compat import lrange from pandas.compat.numpy import np_datetime64_compat from pandas import (DatetimeIndex, Index, date_range, Series, DataFrame, - Timestamp, datetime, offsets, _np_version_under1p8) + Timestamp, datetime, offsets) from pandas.util.testing import assert_series_equal, assert_almost_equal @@ -276,11 +276,7 @@ def test_comparisons_nat(self): np_datetime64_compat('2014-06-01 00:00Z'), np_datetime64_compat('2014-07-01 00:00Z')]) - if _np_version_under1p8: - # cannot test array because np.datetime('nat') returns today's date - cases = [(fidx1, fidx2), (didx1, didx2)] - else: - cases = [(fidx1, fidx2), (didx1, didx2), (didx1, darr)] + cases = [(fidx1, fidx2), (didx1, didx2), (didx1, darr)] # Check pd.NaT is handles as the same as np.nan with tm.assert_produces_warning(None): diff --git a/pandas/tests/indexes/period/test_indexing.py b/pandas/tests/indexes/period/test_indexing.py index d4dac1cf88fff..efc13a56cd77e 100644 --- a/pandas/tests/indexes/period/test_indexing.py +++ b/pandas/tests/indexes/period/test_indexing.py @@ -8,7 +8,7 @@ from pandas.compat import lrange from pandas._libs import tslib from pandas import (PeriodIndex, Series, DatetimeIndex, - period_range, Period, _np_version_under1p9) + period_range, Period) class TestGetItem(object): @@ -149,16 +149,12 @@ def test_getitem_seconds(self): values = ['2014', '2013/02', '2013/01/02', '2013/02/01 9H', '2013/02/01 09:00'] for v in values: - if _np_version_under1p9: - with pytest.raises(ValueError): - idx[v] - else: - # GH7116 - # these show deprecations as we are trying - # to slice with non-integer indexers - # with pytest.raises(IndexError): - # idx[v] - continue + # GH7116 + # these show deprecations as we are trying + # to slice with non-integer indexers + # with pytest.raises(IndexError): + # idx[v] + continue s = Series(np.random.rand(len(idx)), index=idx) tm.assert_series_equal(s['2013/01/01 10:00'], s[3600:3660]) @@ -178,16 +174,12 @@ def test_getitem_day(self): '2013/02/01 09:00'] for v in values: - if _np_version_under1p9: - with pytest.raises(ValueError): - idx[v] - else: - # GH7116 - # these show deprecations as we are trying - # to slice with non-integer indexers - # with pytest.raises(IndexError): - # idx[v] - continue + # GH7116 + # these show deprecations as we are trying + # to slice with non-integer indexers + # with pytest.raises(IndexError): + # idx[v] + continue s = Series(np.random.rand(len(idx)), index=idx) tm.assert_series_equal(s['2013/01'], s[0:31]) diff --git a/pandas/tests/indexes/timedeltas/test_timedelta.py b/pandas/tests/indexes/timedeltas/test_timedelta.py index 59e4b1432b8bc..0b3bd0b03bccf 100644 --- a/pandas/tests/indexes/timedeltas/test_timedelta.py +++ b/pandas/tests/indexes/timedeltas/test_timedelta.py @@ -7,7 +7,7 @@ import pandas.util.testing as tm from pandas import (timedelta_range, date_range, Series, Timedelta, DatetimeIndex, TimedeltaIndex, Index, DataFrame, - Int64Index, _np_version_under1p8) + Int64Index) from pandas.util.testing import (assert_almost_equal, assert_series_equal, assert_index_equal) @@ -379,11 +379,7 @@ def test_comparisons_nat(self): np.timedelta64(1, 'D') + np.timedelta64(2, 's'), np.timedelta64(5, 'D') + np.timedelta64(3, 's')]) - if _np_version_under1p8: - # cannot test array because np.datetime('nat') returns today's date - cases = [(tdidx1, tdidx2)] - else: - cases = [(tdidx1, tdidx2), (tdidx1, tdarr)] + cases = [(tdidx1, tdidx2), (tdidx1, tdarr)] # Check pd.NaT is handles as the same as np.nan for idx1, idx2 in cases: diff --git a/pandas/tests/plotting/common.py b/pandas/tests/plotting/common.py index 3ab443b223f20..dfab539e9474c 100644 --- a/pandas/tests/plotting/common.py +++ b/pandas/tests/plotting/common.py @@ -39,7 +39,8 @@ def _ok_for_gaussian_kde(kind): from scipy.stats import gaussian_kde # noqa except ImportError: return False - return True + + return plotting._compat._mpl_ge_1_5_0() class TestPlotBase(object): diff --git a/pandas/tests/plotting/test_datetimelike.py b/pandas/tests/plotting/test_datetimelike.py index e9c7d806fd65d..cff0c1c0b424e 100644 --- a/pandas/tests/plotting/test_datetimelike.py +++ b/pandas/tests/plotting/test_datetimelike.py @@ -610,6 +610,8 @@ def test_secondary_y_ts(self): @pytest.mark.slow def test_secondary_kde(self): + if not self.mpl_ge_1_5_0: + pytest.skip("mpl is not supported") tm._skip_if_no_scipy() _skip_if_no_scipy_gaussian_kde() diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py index 6d813ac76cc4e..67098529a0111 100644 --- a/pandas/tests/plotting/test_frame.py +++ b/pandas/tests/plotting/test_frame.py @@ -473,7 +473,6 @@ def test_subplots_multiple_axes(self): # TestDataFrameGroupByPlots.test_grouped_box_multiple_axes fig, axes = self.plt.subplots(2, 2) with warnings.catch_warnings(): - warnings.simplefilter('ignore') df = DataFrame(np.random.rand(10, 4), index=list(string.ascii_letters[:10])) @@ -1290,6 +1289,9 @@ def test_boxplot_subplots_return_type(self): def test_kde_df(self): tm._skip_if_no_scipy() _skip_if_no_scipy_gaussian_kde() + if not self.mpl_ge_1_5_0: + pytest.skip("mpl is not supported") + df = DataFrame(randn(100, 4)) ax = _check_plot_works(df.plot, kind='kde') expected = [pprint_thing(c) for c in df.columns] @@ -1311,6 +1313,9 @@ def test_kde_df(self): def test_kde_missing_vals(self): tm._skip_if_no_scipy() _skip_if_no_scipy_gaussian_kde() + if not self.mpl_ge_1_5_0: + pytest.skip("mpl is not supported") + df = DataFrame(np.random.uniform(size=(100, 4))) df.loc[0, 0] = np.nan _check_plot_works(df.plot, kind='kde') @@ -1835,6 +1840,8 @@ def test_hist_colors(self): def test_kde_colors(self): tm._skip_if_no_scipy() _skip_if_no_scipy_gaussian_kde() + if not self.mpl_ge_1_5_0: + pytest.skip("mpl is not supported") from matplotlib import cm @@ -1858,6 +1865,8 @@ def test_kde_colors(self): def test_kde_colors_and_styles_subplots(self): tm._skip_if_no_scipy() _skip_if_no_scipy_gaussian_kde() + if not self.mpl_ge_1_5_0: + pytest.skip("mpl is not supported") from matplotlib import cm default_colors = self._maybe_unpack_cycler(self.plt.rcParams) @@ -2160,71 +2169,74 @@ def test_pie_df_nan(self): @pytest.mark.slow def test_errorbar_plot(self): - d = {'x': np.arange(12), 'y': np.arange(12, 0, -1)} - df = DataFrame(d) - d_err = {'x': np.ones(12) * 0.2, 'y': np.ones(12) * 0.4} - df_err = DataFrame(d_err) - - # check line plots - ax = _check_plot_works(df.plot, yerr=df_err, logy=True) - self._check_has_errorbars(ax, xerr=0, yerr=2) - ax = _check_plot_works(df.plot, yerr=df_err, logx=True, logy=True) - self._check_has_errorbars(ax, xerr=0, yerr=2) - ax = _check_plot_works(df.plot, yerr=df_err, loglog=True) - self._check_has_errorbars(ax, xerr=0, yerr=2) + with warnings.catch_warnings(): + d = {'x': np.arange(12), 'y': np.arange(12, 0, -1)} + df = DataFrame(d) + d_err = {'x': np.ones(12) * 0.2, 'y': np.ones(12) * 0.4} + df_err = DataFrame(d_err) - kinds = ['line', 'bar', 'barh'] - for kind in kinds: - ax = _check_plot_works(df.plot, yerr=df_err['x'], kind=kind) + # check line plots + ax = _check_plot_works(df.plot, yerr=df_err, logy=True) self._check_has_errorbars(ax, xerr=0, yerr=2) - ax = _check_plot_works(df.plot, yerr=d_err, kind=kind) + ax = _check_plot_works(df.plot, yerr=df_err, logx=True, logy=True) self._check_has_errorbars(ax, xerr=0, yerr=2) - ax = _check_plot_works(df.plot, yerr=df_err, xerr=df_err, - kind=kind) - self._check_has_errorbars(ax, xerr=2, yerr=2) - ax = _check_plot_works(df.plot, yerr=df_err['x'], xerr=df_err['x'], - kind=kind) - self._check_has_errorbars(ax, xerr=2, yerr=2) - ax = _check_plot_works(df.plot, xerr=0.2, yerr=0.2, kind=kind) - self._check_has_errorbars(ax, xerr=2, yerr=2) - # _check_plot_works adds an ax so catch warning. see GH #13188 - with tm.assert_produces_warning(UserWarning): + ax = _check_plot_works(df.plot, yerr=df_err, loglog=True) + self._check_has_errorbars(ax, xerr=0, yerr=2) + + kinds = ['line', 'bar', 'barh'] + for kind in kinds: + ax = _check_plot_works(df.plot, yerr=df_err['x'], kind=kind) + self._check_has_errorbars(ax, xerr=0, yerr=2) + ax = _check_plot_works(df.plot, yerr=d_err, kind=kind) + self._check_has_errorbars(ax, xerr=0, yerr=2) + ax = _check_plot_works(df.plot, yerr=df_err, xerr=df_err, + kind=kind) + self._check_has_errorbars(ax, xerr=2, yerr=2) + ax = _check_plot_works(df.plot, yerr=df_err['x'], + xerr=df_err['x'], + kind=kind) + self._check_has_errorbars(ax, xerr=2, yerr=2) + ax = _check_plot_works(df.plot, xerr=0.2, yerr=0.2, kind=kind) + self._check_has_errorbars(ax, xerr=2, yerr=2) + + # _check_plot_works adds an ax so catch warning. see GH #13188 axes = _check_plot_works(df.plot, yerr=df_err, xerr=df_err, subplots=True, kind=kind) - self._check_has_errorbars(axes, xerr=1, yerr=1) - - ax = _check_plot_works((df + 1).plot, yerr=df_err, - xerr=df_err, kind='bar', log=True) - self._check_has_errorbars(ax, xerr=2, yerr=2) + self._check_has_errorbars(axes, xerr=1, yerr=1) - # yerr is raw error values - ax = _check_plot_works(df['y'].plot, yerr=np.ones(12) * 0.4) - self._check_has_errorbars(ax, xerr=0, yerr=1) - ax = _check_plot_works(df.plot, yerr=np.ones((2, 12)) * 0.4) - self._check_has_errorbars(ax, xerr=0, yerr=2) + ax = _check_plot_works((df + 1).plot, yerr=df_err, + xerr=df_err, kind='bar', log=True) + self._check_has_errorbars(ax, xerr=2, yerr=2) - # yerr is iterator - import itertools - ax = _check_plot_works(df.plot, yerr=itertools.repeat(0.1, len(df))) - self._check_has_errorbars(ax, xerr=0, yerr=2) + # yerr is raw error values + ax = _check_plot_works(df['y'].plot, yerr=np.ones(12) * 0.4) + self._check_has_errorbars(ax, xerr=0, yerr=1) + ax = _check_plot_works(df.plot, yerr=np.ones((2, 12)) * 0.4) + self._check_has_errorbars(ax, xerr=0, yerr=2) - # yerr is column name - for yerr in ['yerr', u('誤差')]: - s_df = df.copy() - s_df[yerr] = np.ones(12) * 0.2 - ax = _check_plot_works(s_df.plot, yerr=yerr) + # yerr is iterator + import itertools + ax = _check_plot_works(df.plot, + yerr=itertools.repeat(0.1, len(df))) self._check_has_errorbars(ax, xerr=0, yerr=2) - ax = _check_plot_works(s_df.plot, y='y', x='x', yerr=yerr) - self._check_has_errorbars(ax, xerr=0, yerr=1) - with pytest.raises(ValueError): - df.plot(yerr=np.random.randn(11)) + # yerr is column name + for yerr in ['yerr', u('誤差')]: + s_df = df.copy() + s_df[yerr] = np.ones(12) * 0.2 + ax = _check_plot_works(s_df.plot, yerr=yerr) + self._check_has_errorbars(ax, xerr=0, yerr=2) + ax = _check_plot_works(s_df.plot, y='y', x='x', yerr=yerr) + self._check_has_errorbars(ax, xerr=0, yerr=1) - df_err = DataFrame({'x': ['zzz'] * 12, 'y': ['zzz'] * 12}) - with pytest.raises((ValueError, TypeError)): - df.plot(yerr=df_err) + with pytest.raises(ValueError): + df.plot(yerr=np.random.randn(11)) + + df_err = DataFrame({'x': ['zzz'] * 12, 'y': ['zzz'] * 12}) + with pytest.raises((ValueError, TypeError)): + df.plot(yerr=df_err) @pytest.mark.slow def test_errorbar_with_integer_column_names(self): @@ -2262,33 +2274,34 @@ def test_errorbar_with_partial_columns(self): @pytest.mark.slow def test_errorbar_timeseries(self): - d = {'x': np.arange(12), 'y': np.arange(12, 0, -1)} - d_err = {'x': np.ones(12) * 0.2, 'y': np.ones(12) * 0.4} + with warnings.catch_warnings(): + d = {'x': np.arange(12), 'y': np.arange(12, 0, -1)} + d_err = {'x': np.ones(12) * 0.2, 'y': np.ones(12) * 0.4} - # check time-series plots - ix = date_range('1/1/2000', '1/1/2001', freq='M') - tdf = DataFrame(d, index=ix) - tdf_err = DataFrame(d_err, index=ix) + # check time-series plots + ix = date_range('1/1/2000', '1/1/2001', freq='M') + tdf = DataFrame(d, index=ix) + tdf_err = DataFrame(d_err, index=ix) - kinds = ['line', 'bar', 'barh'] - for kind in kinds: - ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind) - self._check_has_errorbars(ax, xerr=0, yerr=2) - ax = _check_plot_works(tdf.plot, yerr=d_err, kind=kind) - self._check_has_errorbars(ax, xerr=0, yerr=2) - ax = _check_plot_works(tdf.plot, y='y', yerr=tdf_err['x'], - kind=kind) - self._check_has_errorbars(ax, xerr=0, yerr=1) - ax = _check_plot_works(tdf.plot, y='y', yerr='x', kind=kind) - self._check_has_errorbars(ax, xerr=0, yerr=1) - ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind) - self._check_has_errorbars(ax, xerr=0, yerr=2) - # _check_plot_works adds an ax so catch warning. see GH #13188 - with tm.assert_produces_warning(UserWarning): + kinds = ['line', 'bar', 'barh'] + for kind in kinds: + ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind) + self._check_has_errorbars(ax, xerr=0, yerr=2) + ax = _check_plot_works(tdf.plot, yerr=d_err, kind=kind) + self._check_has_errorbars(ax, xerr=0, yerr=2) + ax = _check_plot_works(tdf.plot, y='y', yerr=tdf_err['x'], + kind=kind) + self._check_has_errorbars(ax, xerr=0, yerr=1) + ax = _check_plot_works(tdf.plot, y='y', yerr='x', kind=kind) + self._check_has_errorbars(ax, xerr=0, yerr=1) + ax = _check_plot_works(tdf.plot, yerr=tdf_err, kind=kind) + self._check_has_errorbars(ax, xerr=0, yerr=2) + + # _check_plot_works adds an ax so catch warning. see GH #13188 axes = _check_plot_works(tdf.plot, kind=kind, yerr=tdf_err, subplots=True) - self._check_has_errorbars(axes, xerr=0, yerr=1) + self._check_has_errorbars(axes, xerr=0, yerr=1) def test_errorbar_asymmetrical(self): diff --git a/pandas/tests/plotting/test_misc.py b/pandas/tests/plotting/test_misc.py index 684a943fb5a69..c4795ea1e1eca 100644 --- a/pandas/tests/plotting/test_misc.py +++ b/pandas/tests/plotting/test_misc.py @@ -4,7 +4,7 @@ import pytest -from pandas import Series, DataFrame +from pandas import DataFrame from pandas.compat import lmap import pandas.util.testing as tm @@ -13,8 +13,7 @@ from numpy.random import randn import pandas.plotting as plotting -from pandas.tests.plotting.common import (TestPlotBase, _check_plot_works, - _ok_for_gaussian_kde) +from pandas.tests.plotting.common import TestPlotBase, _check_plot_works tm._skip_if_no_mpl() @@ -52,46 +51,6 @@ def test_bootstrap_plot(self): class TestDataFramePlots(TestPlotBase): - @pytest.mark.slow - def test_scatter_plot_legacy(self): - tm._skip_if_no_scipy() - - df = DataFrame(randn(100, 2)) - - def scat(**kwds): - return plotting.scatter_matrix(df, **kwds) - - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat) - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat, marker='+') - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat, vmin=0) - if _ok_for_gaussian_kde('kde'): - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat, diagonal='kde') - if _ok_for_gaussian_kde('density'): - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat, diagonal='density') - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat, diagonal='hist') - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat, range_padding=.1) - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat, color='rgb') - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat, c='rgb') - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat, facecolor='rgb') - - def scat2(x, y, by=None, ax=None, figsize=None): - return plotting._core.scatter_plot(df, x, y, by, ax, figsize=None) - - _check_plot_works(scat2, x=0, y=1) - grouper = Series(np.repeat([1, 2, 3, 4, 5], 20), df.index) - with tm.assert_produces_warning(UserWarning): - _check_plot_works(scat2, x=0, y=1, by=grouper) - def test_scatter_matrix_axis(self): tm._skip_if_no_scipy() scatter_matrix = plotting.scatter_matrix diff --git a/pandas/tests/plotting/test_series.py b/pandas/tests/plotting/test_series.py index 9c9011ba1ca7b..8164ad74a190a 100644 --- a/pandas/tests/plotting/test_series.py +++ b/pandas/tests/plotting/test_series.py @@ -571,6 +571,9 @@ def test_plot_fails_with_dupe_color_and_style(self): @pytest.mark.slow def test_hist_kde(self): + if not self.mpl_ge_1_5_0: + pytest.skip("mpl is not supported") + _, ax = self.plt.subplots() ax = self.ts.plot.hist(logy=True, ax=ax) self._check_ax_scales(ax, yaxis='log') @@ -596,6 +599,9 @@ def test_hist_kde(self): def test_kde_kwargs(self): tm._skip_if_no_scipy() _skip_if_no_scipy_gaussian_kde() + if not self.mpl_ge_1_5_0: + pytest.skip("mpl is not supported") + from numpy import linspace _check_plot_works(self.ts.plot.kde, bw_method=.5, ind=linspace(-100, 100, 20)) @@ -611,6 +617,9 @@ def test_kde_kwargs(self): def test_kde_missing_vals(self): tm._skip_if_no_scipy() _skip_if_no_scipy_gaussian_kde() + if not self.mpl_ge_1_5_0: + pytest.skip("mpl is not supported") + s = Series(np.random.uniform(size=50)) s[0] = np.nan axes = _check_plot_works(s.plot.kde) @@ -638,6 +647,9 @@ def test_hist_kwargs(self): @pytest.mark.slow def test_hist_kde_color(self): + if not self.mpl_ge_1_5_0: + pytest.skip("mpl is not supported") + _, ax = self.plt.subplots() ax = self.ts.plot.hist(logy=True, bins=10, color='b', ax=ax) self._check_ax_scales(ax, yaxis='log') diff --git a/pandas/tests/series/test_operators.py b/pandas/tests/series/test_operators.py index 4888f8fe996b6..114a055de8195 100644 --- a/pandas/tests/series/test_operators.py +++ b/pandas/tests/series/test_operators.py @@ -14,8 +14,7 @@ import pandas as pd from pandas import (Index, Series, DataFrame, isna, bdate_range, - NaT, date_range, timedelta_range, - _np_version_under1p8) + NaT, date_range, timedelta_range) from pandas.core.indexes.datetimes import Timestamp from pandas.core.indexes.timedeltas import Timedelta import pandas.core.nanops as nanops @@ -687,14 +686,13 @@ def run_ops(ops, get_ser, test_ser): assert_series_equal(result, exp) # odd numpy behavior with scalar timedeltas - if not _np_version_under1p8: - result = td1[0] + dt1 - exp = (dt1.dt.tz_localize(None) + td1[0]).dt.tz_localize(tz) - assert_series_equal(result, exp) + result = td1[0] + dt1 + exp = (dt1.dt.tz_localize(None) + td1[0]).dt.tz_localize(tz) + assert_series_equal(result, exp) - result = td2[0] + dt2 - exp = (dt2.dt.tz_localize(None) + td2[0]).dt.tz_localize(tz) - assert_series_equal(result, exp) + result = td2[0] + dt2 + exp = (dt2.dt.tz_localize(None) + td2[0]).dt.tz_localize(tz) + assert_series_equal(result, exp) result = dt1 - td1[0] exp = (dt1.dt.tz_localize(None) - td1[0]).dt.tz_localize(tz) diff --git a/pandas/tests/series/test_quantile.py b/pandas/tests/series/test_quantile.py index 21379641a78d8..cf5e3fe4f29b0 100644 --- a/pandas/tests/series/test_quantile.py +++ b/pandas/tests/series/test_quantile.py @@ -1,11 +1,10 @@ # coding=utf-8 # pylint: disable-msg=E1101,W0612 -import pytest import numpy as np import pandas as pd -from pandas import (Index, Series, _np_version_under1p9) +from pandas import Index, Series from pandas.core.indexes.datetimes import Timestamp from pandas.core.dtypes.common import is_integer import pandas.util.testing as tm @@ -68,8 +67,6 @@ def test_quantile_multi(self): [], dtype=float)) tm.assert_series_equal(result, expected) - @pytest.mark.skipif(_np_version_under1p9, - reason="Numpy version is under 1.9") def test_quantile_interpolation(self): # see gh-10174 @@ -82,8 +79,6 @@ def test_quantile_interpolation(self): # test with and without interpolation keyword assert q == q1 - @pytest.mark.skipif(_np_version_under1p9, - reason="Numpy version is under 1.9") def test_quantile_interpolation_dtype(self): # GH #10174 @@ -96,26 +91,6 @@ def test_quantile_interpolation_dtype(self): assert q == np.percentile(np.array([1, 3, 4]), 50) assert is_integer(q) - @pytest.mark.skipif(not _np_version_under1p9, - reason="Numpy version is greater 1.9") - def test_quantile_interpolation_np_lt_1p9(self): - # GH #10174 - - # interpolation = linear (default case) - q = self.ts.quantile(0.1, interpolation='linear') - assert q == np.percentile(self.ts.valid(), 10) - q1 = self.ts.quantile(0.1) - assert q1 == np.percentile(self.ts.valid(), 10) - - # interpolation other than linear - msg = "Interpolation methods other than " - with tm.assert_raises_regex(ValueError, msg): - self.ts.quantile(0.9, interpolation='nearest') - - # object dtype - with tm.assert_raises_regex(ValueError, msg): - Series(self.ts, dtype=object).quantile(0.7, interpolation='higher') - def test_quantile_nan(self): # GH 13098 diff --git a/pandas/tests/series/test_rank.py b/pandas/tests/series/test_rank.py index ff489eb7f15b1..4dbc38fc9f4a6 100644 --- a/pandas/tests/series/test_rank.py +++ b/pandas/tests/series/test_rank.py @@ -29,6 +29,7 @@ class TestSeriesRank(TestData): def test_rank(self): tm._skip_if_no_scipy() + pytest.importorskip('scipy.stats.special') from scipy.stats import rankdata self.ts[::2] = np.nan @@ -248,6 +249,7 @@ def _check(s, expected, method='average'): def test_rank_methods_series(self): tm.skip_if_no_package('scipy', min_version='0.13', app='scipy.stats.rankdata') + pytest.importorskip('scipy.stats.special') import scipy from scipy.stats import rankdata diff --git a/pandas/tests/sparse/test_array.py b/pandas/tests/sparse/test_array.py index 4ce03f72dbba6..b0a9182a265fe 100644 --- a/pandas/tests/sparse/test_array.py +++ b/pandas/tests/sparse/test_array.py @@ -8,7 +8,6 @@ from numpy import nan import numpy as np -from pandas import _np_version_under1p8 from pandas.core.sparse.api import SparseArray, SparseSeries from pandas._libs.sparse import IntIndex from pandas.util.testing import assert_almost_equal @@ -150,10 +149,8 @@ def test_take(self): assert np.isnan(self.arr.take(0)) assert np.isscalar(self.arr.take(2)) - # np.take in < 1.8 doesn't support scalar indexing - if not _np_version_under1p8: - assert self.arr.take(2) == np.take(self.arr_data, 2) - assert self.arr.take(6) == np.take(self.arr_data, 6) + assert self.arr.take(2) == np.take(self.arr_data, 2) + assert self.arr.take(6) == np.take(self.arr_data, 6) exp = SparseArray(np.take(self.arr_data, [2, 3])) tm.assert_sp_array_equal(self.arr.take([2, 3]), exp) diff --git a/pandas/tests/test_nanops.py b/pandas/tests/test_nanops.py index 2a22fc9d32919..9305504f8d5e3 100644 --- a/pandas/tests/test_nanops.py +++ b/pandas/tests/test_nanops.py @@ -8,7 +8,7 @@ import numpy as np import pandas as pd -from pandas import Series, isna, _np_version_under1p9 +from pandas import Series, isna from pandas.core.dtypes.common import is_integer_dtype import pandas.core.nanops as nanops import pandas.util.testing as tm @@ -340,15 +340,13 @@ def test_nanmean_overflow(self): # In the previous implementation mean can overflow for int dtypes, it # is now consistent with numpy - # numpy < 1.9.0 is not computing this correctly - if not _np_version_under1p9: - for a in [2 ** 55, -2 ** 55, 20150515061816532]: - s = Series(a, index=range(500), dtype=np.int64) - result = s.mean() - np_result = s.values.mean() - assert result == a - assert result == np_result - assert result.dtype == np.float64 + for a in [2 ** 55, -2 ** 55, 20150515061816532]: + s = Series(a, index=range(500), dtype=np.int64) + result = s.mean() + np_result = s.values.mean() + assert result == a + assert result == np_result + assert result.dtype == np.float64 def test_returned_dtype(self): diff --git a/pandas/tests/test_resample.py b/pandas/tests/test_resample.py index d938d5bf9f3ab..d42e37048d87f 100644 --- a/pandas/tests/test_resample.py +++ b/pandas/tests/test_resample.py @@ -1688,7 +1688,7 @@ def test_resample_dtype_preservation(self): def test_resample_dtype_coerceion(self): - pytest.importorskip('scipy') + pytest.importorskip('scipy.interpolate') # GH 16361 df = {"a": [1, 3, 1, 4]} diff --git a/pandas/tests/tools/test_numeric.py b/pandas/tests/tools/test_numeric.py index 664a97640387e..1d13ba93ba759 100644 --- a/pandas/tests/tools/test_numeric.py +++ b/pandas/tests/tools/test_numeric.py @@ -3,7 +3,7 @@ import numpy as np import pandas as pd -from pandas import to_numeric, _np_version_under1p9 +from pandas import to_numeric from pandas.util import testing as tm from numpy import iinfo @@ -355,9 +355,6 @@ def test_downcast(self): def test_downcast_limits(self): # Test the limits of each downcast. Bug: #14401. - # Check to make sure numpy is new enough to run this test. - if _np_version_under1p9: - pytest.skip("Numpy version is under 1.9") i = 'integer' u = 'unsigned' diff --git a/setup.py b/setup.py index a912b25328954..04a5684c20fcd 100755 --- a/setup.py +++ b/setup.py @@ -45,7 +45,7 @@ def is_platform_mac(): _have_setuptools = False setuptools_kwargs = {} -min_numpy_ver = '1.7.0' +min_numpy_ver = '1.9.0' if sys.version_info[0] >= 3: setuptools_kwargs = {