DEPS: drop numpy < 1.12

ci/azure-macos-35.yaml

@@ -11,7 +11,7 @@ dependencies:
   - matplotlib
   - nomkl
   - numexpr
-  - numpy=1.10.4
+  - numpy=1.12.1
   - openpyxl=2.5.5
   - pytables
   - python=3.5*

ci/circle-27-compat.yaml

@@ -7,7 +7,7 @@ dependencies:
   - cython=0.28.2
   - jinja2=2.8
   - numexpr=2.4.4 # we test that we correctly don't use an unsupported numexpr
-  - numpy=1.9.3
+  - numpy=1.12.1
   - openpyxl=2.5.5
   - psycopg2
   - pytables=3.2.2

ci/travis-27-locale.yaml

@@ -7,7 +7,7 @@ dependencies:
   - cython=0.28.2
   - lxml
   - matplotlib=1.4.3
-  - numpy=1.9.3
+  - numpy=1.12.1
   - openpyxl=2.4.0
   - python-dateutil
   - python-blosc

doc/source/install.rst

@@ -225,7 +225,7 @@ Dependencies
 ------------
 
 * `setuptools <https://setuptools.readthedocs.io/en/latest/>`__: 24.2.0 or higher
-* `NumPy <http://www.numpy.org>`__: 1.9.0 or higher
+* `NumPy <http://www.numpy.org>`__: 1.12.0 or higher
 * `python-dateutil <https://dateutil.readthedocs.io/en/stable/>`__: 2.5.0 or higher
 * `pytz <http://pytz.sourceforge.net/>`__
 

doc/source/whatsnew/v0.24.0.txt

@@ -199,8 +199,22 @@ Other Enhancements
 
 Backwards incompatible API changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
 - A newly constructed empty :class:`DataFrame` with integer as the ``dtype`` will now only be cast to ``float64`` if ``index`` is specified (:issue:`22858`)
 
+.. _whatsnew_0240.api_breaking.deps:
+
+Dependencies have increased minimum versions
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+We have updated our minimum supported versions of dependencies (:issue:`21242`).
+We now require:
+
++-----------------+-----------------+----------+---------------+
+| Package         | Minimum Version | Required |     Issue     |
++=================+=================+==========+===============+
+| numpy           | 1.12.0          |    X     | :issue:`21242`|
++-----------------+-----------------+----------+---------------+
 
 .. _whatsnew_0240.api_breaking.interval_values:
 

pandas/compat/numpy/__init__.py

@@ -9,19 +9,16 @@
 # numpy versioning
 _np_version = np.__version__
 _nlv = LooseVersion(_np_version)
-_np_version_under1p10 = _nlv < LooseVersion('1.10')
-_np_version_under1p11 = _nlv < LooseVersion('1.11')
-_np_version_under1p12 = _nlv < LooseVersion('1.12')
 _np_version_under1p13 = _nlv < LooseVersion('1.13')
 _np_version_under1p14 = _nlv < LooseVersion('1.14')
 _np_version_under1p15 = _nlv < LooseVersion('1.15')
 
 
-if _nlv < '1.9':
+if _nlv < '1.12':
     raise ImportError('this version of pandas is incompatible with '
-                      'numpy < 1.9.0\n'
+                      'numpy < 1.12.0\n'
                       'your numpy version is {0}.\n'
-                      'Please upgrade numpy to >= 1.9.0 to use '
+                      'Please upgrade numpy to >= 1.12.0 to use '
                       'this pandas version'.format(_np_version))
 
 
@@ -43,9 +40,7 @@ def np_datetime64_compat(s, *args, **kwargs):
     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'
     """
-
-    if not _np_version_under1p11:
-        s = tz_replacer(s)
+    s = tz_replacer(s)
     return np.datetime64(s, *args, **kwargs)
 
 
@@ -56,23 +51,17 @@ def np_array_datetime64_compat(arr, *args, **kwargs):
     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'
     """
-
-    if not _np_version_under1p11:
-
-        # 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)
+    # 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_under1p10',
-           '_np_version_under1p11',
-           '_np_version_under1p12',
            '_np_version_under1p13',
            '_np_version_under1p14',
            '_np_version_under1p15'

pandas/core/algorithms.py

@@ -30,7 +30,6 @@
     ensure_platform_int, ensure_object,
     ensure_float64, ensure_uint64,
     ensure_int64)
-from pandas.compat.numpy import _np_version_under1p10
 from pandas.core.dtypes.missing import isna, na_value_for_dtype
 
 from pandas.core import common as com
@@ -914,15 +913,7 @@ def _broadcast(arr_or_scalar, shape):
         """
         Helper function to broadcast arrays / scalars to the desired shape.
         """
-        if _np_version_under1p10:
-            if is_scalar(arr_or_scalar):
-                out = np.empty(shape)
-                out.fill(arr_or_scalar)
-            else:
-                out = arr_or_scalar
-        else:
-            out = np.broadcast_to(arr_or_scalar, shape)
-        return out
+        return np.broadcast_to(arr_or_scalar, shape)
 
     # For performance reasons, we broadcast 'b' to the new array 'b2'
     # so that it has the same size as 'arr'.

pandas/tests/arithmetic/test_period.py

@@ -15,9 +15,7 @@
 
 import pandas.core.indexes.period as period
 from pandas.core import ops
-from pandas import (
-    Period, PeriodIndex, period_range, Series,
-    _np_version_under1p10)
+from pandas import Period, PeriodIndex, period_range, Series
 
 
 # ------------------------------------------------------------------
@@ -837,20 +835,14 @@ def test_pi_ops_errors(self, ng):
             with pytest.raises(TypeError):
                 np.add(obj, ng)
 
-            if _np_version_under1p10:
-                assert np.add(ng, obj) is NotImplemented
-            else:
-                with pytest.raises(TypeError):
-                    np.add(ng, obj)
+            with pytest.raises(TypeError):
+                np.add(ng, obj)
 
             with pytest.raises(TypeError):
                 np.subtract(obj, ng)
 
-            if _np_version_under1p10:
-                assert np.subtract(ng, obj) is NotImplemented
-            else:
-                with pytest.raises(TypeError):
-                    np.subtract(ng, obj)
+            with pytest.raises(TypeError):
+                np.subtract(ng, obj)
 
     def test_pi_ops_nat(self):
         idx = PeriodIndex(['2011-01', '2011-02', 'NaT', '2011-04'],
@@ -954,10 +946,7 @@ def test_pi_sub_period(self):
         tm.assert_index_equal(result, exp)
 
         result = np.subtract(pd.Period('2012-01', freq='M'), idx)
-        if _np_version_under1p10:
-            assert result is NotImplemented
-        else:
-            tm.assert_index_equal(result, exp)
+        tm.assert_index_equal(result, exp)
 
         exp = pd.TimedeltaIndex([np.nan, np.nan, np.nan, np.nan], name='idx')
         tm.assert_index_equal(idx - pd.Period('NaT', freq='M'), exp)

pandas/tests/frame/test_analytics.py

@@ -15,7 +15,6 @@
 from pandas.compat import lrange, PY35
 from pandas import (compat, isna, notna, DataFrame, Series,
                     MultiIndex, date_range, Timestamp, Categorical,
-                    _np_version_under1p12,
                     to_datetime, to_timedelta)
 import pandas as pd
 import pandas.core.nanops as nanops
@@ -2021,9 +2020,6 @@ def test_dot(self):
 
     @pytest.mark.skipif(not PY35,
                         reason='matmul supported for Python>=3.5')
-    @pytest.mark.xfail(
-        _np_version_under1p12,
-        reason="unpredictable return types under numpy < 1.12")
     def test_matmul(self):
         # matmul test is for GH 10259
         a = DataFrame(np.random.randn(3, 4), index=['a', 'b', 'c'],

pandas/tests/frame/test_quantile.py

@@ -6,7 +6,7 @@
 import pytest
 import numpy as np
 
-from pandas import (DataFrame, Series, Timestamp, _np_version_under1p11)
+from pandas import DataFrame, Series, Timestamp
 import pandas as pd
 
 from pandas.util.testing import assert_series_equal, assert_frame_equal
@@ -154,12 +154,8 @@ def test_quantile_interpolation(self):
         result = df.quantile([.25, .5], interpolation='midpoint')
 
         # https://github.com/numpy/numpy/issues/7163
-        if _np_version_under1p11:
-            expected = DataFrame([[1.5, 1.5, 1.5], [2.5, 2.5, 2.5]],
-                                 index=[.25, .5], columns=['a', 'b', 'c'])
-        else:
-            expected = DataFrame([[1.5, 1.5, 1.5], [2.0, 2.0, 2.0]],
-                                 index=[.25, .5], columns=['a', 'b', 'c'])
+        expected = DataFrame([[1.5, 1.5, 1.5], [2.0, 2.0, 2.0]],
+                             index=[.25, .5], columns=['a', 'b', 'c'])
         assert_frame_equal(result, expected)
 
     def test_quantile_multi(self):

pandas/tests/indexes/datetimes/test_ops.py

@@ -7,8 +7,7 @@
 import pandas._libs.tslib as tslib
 import pandas.util.testing as tm
 from pandas import (DatetimeIndex, PeriodIndex, Series, Timestamp,
-                    date_range, _np_version_under1p10, Index,
-                    bdate_range)
+                    date_range, bdate_range, Index)
 from pandas.tseries.offsets import BMonthEnd, CDay, BDay, Day, Hour
 from pandas.tests.test_base import Ops
 from pandas.core.dtypes.generic import ABCDateOffset
@@ -89,12 +88,11 @@ def test_numpy_minmax(self):
         assert np.argmin(dr) == 0
         assert np.argmax(dr) == 5
 
-        if not _np_version_under1p10:
-            errmsg = "the 'out' parameter is not supported"
-            tm.assert_raises_regex(
-                ValueError, errmsg, np.argmin, dr, out=0)
-            tm.assert_raises_regex(
-                ValueError, errmsg, np.argmax, dr, out=0)
+        errmsg = "the 'out' parameter is not supported"
+        tm.assert_raises_regex(
+            ValueError, errmsg, np.argmin, dr, out=0)
+        tm.assert_raises_regex(
+            ValueError, errmsg, np.argmax, dr, out=0)
 
     def test_repeat_range(self, tz_naive_fixture):
         tz = tz_naive_fixture

pandas/tests/indexes/period/test_ops.py

@@ -5,8 +5,7 @@
 import pandas as pd
 import pandas._libs.tslib as tslib
 import pandas.util.testing as tm
-from pandas import (DatetimeIndex, PeriodIndex, Series, Period,
-                    _np_version_under1p10, Index)
+from pandas import DatetimeIndex, PeriodIndex, Series, Period, Index
 
 from pandas.tests.test_base import Ops
 
@@ -73,12 +72,11 @@ def test_numpy_minmax(self):
         assert np.argmin(pr) == 0
         assert np.argmax(pr) == 5
 
-        if not _np_version_under1p10:
-            errmsg = "the 'out' parameter is not supported"
-            tm.assert_raises_regex(
-                ValueError, errmsg, np.argmin, pr, out=0)
-            tm.assert_raises_regex(
-                ValueError, errmsg, np.argmax, pr, out=0)
+        errmsg = "the 'out' parameter is not supported"
+        tm.assert_raises_regex(
+            ValueError, errmsg, np.argmin, pr, out=0)
+        tm.assert_raises_regex(
+            ValueError, errmsg, np.argmax, pr, out=0)
 
     def test_resolution(self):
         for freq, expected in zip(['A', 'Q', 'M', 'D', 'H',

pandas/tests/indexes/period/test_partial_slicing.py

@@ -5,7 +5,7 @@
 import pandas as pd
 from pandas.util import testing as tm
 from pandas import (Series, period_range, DatetimeIndex, PeriodIndex,
-                    DataFrame, _np_version_under1p12, Period)
+                    DataFrame, Period)
 
 
 class TestPeriodIndex(object):
@@ -68,16 +68,15 @@ def test_range_slice_day(self):
         didx = DatetimeIndex(start='2013/01/01', freq='D', periods=400)
         pidx = PeriodIndex(start='2013/01/01', freq='D', periods=400)
 
-        # changed to TypeError in 1.12
+        # exception changed to TypeError in 1.12
         # https://github.com/numpy/numpy/pull/6271
-        exc = IndexError if _np_version_under1p12 else TypeError
 
         for idx in [didx, pidx]:
             # slices against index should raise IndexError
             values = ['2014', '2013/02', '2013/01/02', '2013/02/01 9H',
                       '2013/02/01 09:00']
             for v in values:
-                with pytest.raises(exc):
+                with pytest.raises(TypeError):
                     idx[v:]
 
             s = Series(np.random.rand(len(idx)), index=idx)
@@ -89,7 +88,7 @@ def test_range_slice_day(self):
 
             invalid = ['2013/02/01 9H', '2013/02/01 09:00']
             for v in invalid:
-                with pytest.raises(exc):
+                with pytest.raises(TypeError):
                     idx[v:]
 
     def test_range_slice_seconds(self):
@@ -98,16 +97,15 @@ def test_range_slice_seconds(self):
                              periods=4000)
         pidx = PeriodIndex(start='2013/01/01 09:00:00', freq='S', periods=4000)
 
-        # changed to TypeError in 1.12
+        # exception changed to TypeError in 1.12
         # https://github.com/numpy/numpy/pull/6271
-        exc = IndexError if _np_version_under1p12 else TypeError
 
         for idx in [didx, pidx]:
             # slices against index should raise IndexError
             values = ['2014', '2013/02', '2013/01/02', '2013/02/01 9H',
                       '2013/02/01 09:00']
             for v in values:
-                with pytest.raises(exc):
+                with pytest.raises(TypeError):
                     idx[v:]
 
             s = Series(np.random.rand(len(idx)), index=idx)

pandas/tests/indexes/timedeltas/test_ops.py

@@ -5,10 +5,8 @@
 
 import pandas as pd
 import pandas.util.testing as tm
-from pandas import to_timedelta
 from pandas import (Series, Timedelta, Timestamp, TimedeltaIndex,
-                    timedelta_range,
-                    _np_version_under1p10)
+                    timedelta_range, to_timedelta)
 from pandas._libs.tslib import iNaT
 from pandas.tests.test_base import Ops
 from pandas.tseries.offsets import Day, Hour
@@ -68,12 +66,11 @@ def test_numpy_minmax(self):
         assert np.argmin(td) == 0
         assert np.argmax(td) == 5
 
-        if not _np_version_under1p10:
-            errmsg = "the 'out' parameter is not supported"
-            tm.assert_raises_regex(
-                ValueError, errmsg, np.argmin, td, out=0)
-            tm.assert_raises_regex(
-                ValueError, errmsg, np.argmax, td, out=0)
+        errmsg = "the 'out' parameter is not supported"
+        tm.assert_raises_regex(
+            ValueError, errmsg, np.argmin, td, out=0)
+        tm.assert_raises_regex(
+            ValueError, errmsg, np.argmax, td, out=0)
 
     def test_value_counts_unique(self):
         # GH 7735