Merge 4eaae30 into 902ea10

hpat/datatypes/hpat_pandas_series_functions.py

@@ -534,6 +534,54 @@ def hpat_pandas_series_copy_impl(self, deep=True):
             return hpat_pandas_series_copy_impl
 
 
+# @overload_method(SeriesType, 'head')
+# def hpat_pandas_series_head(self, n=5):
+#     """
+#     Pandas Series method :meth:`pandas.Series.head` implementation.
+#
+#     .. only:: developer
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head1
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_default1
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_index1
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_index2
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_index3
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_index4
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_parallel1
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_index_parallel1
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_index_parallel2
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_noidx
+#        Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_head_idx
+#
+#     Parameters
+#     -----------
+#     n: :obj:`int`
+#                input argument, default 5
+#     Returns
+#     -------
+#     :obj:`pandas.Series`
+#          returns The first n rows of the caller object.
+#     """
+#
+#     _func_name = 'Method head().'
+#
+#     if not isinstance(self, SeriesType):
+#         raise TypingError('{} The object must be a pandas.series. Given: {}'.format(_func_name, self))
+#
+#     if not isinstance(n, (types.Integer, types.Omitted)) and n != 5:
+#         raise TypingError('{} The parameter must be an integer type. Given type n: {}'.format(_func_name, n))
+#
+#     if isinstance(self.index, types.NoneType):
+#         def hpat_pandas_series_head_impl(self, n=5):
+#             return pandas.Series(self._data[:n])
+#
+#         return hpat_pandas_series_head_impl
+#     else:
+#         def hpat_pandas_series_head_index_impl(self, n=5):
+#             return pandas.Series(self._data[:n], self._index[:n])
+#
+#         return hpat_pandas_series_head_index_impl
+
+
 @overload_method(SeriesType, 'groupby')
 def hpat_pandas_series_groupby(
         self,

hpat/hiframes/pd_series_ext.py

@@ -996,6 +996,7 @@ def generic_expand_cumulative_series(self, args, kws):
                            'resolve_take', 'resolve_max', 'resolve_min', 'resolve_nunique',
                            'resolve_prod', 'resolve_count']
 
+
 # use ArrayAttribute for attributes not defined in SeriesAttribute
 for attr, func in numba.typing.arraydecl.ArrayAttribute.__dict__.items():
     if (attr.startswith('resolve_')

hpat/tests/test_series.py

@@ -1988,6 +1988,70 @@ def test_impl(S):
         pd.testing.assert_series_equal(hpat_func(S[start:end]), test_impl(S))
         self.assertTrue(count_array_OneDs() > 0)
 
+    def test_series_head_noidx(self):
+        def test_impl(S):
+            return S.head()
+
+        def test_impl_param(S, n):
+            return S.head(n)
+
+        hpat_func = hpat.jit(test_impl)
+
+        data_test = [[6, 6, 2, 1, 3, 3, 2, 1, 2],
+                     [1.1, 0.3, 2.1, 1, 3, 0.3, 2.1, 1.1, 2.2],
+                     [6, 6.1, 2.2, 1, 3, 0, 2.2, 1, 2],
+                     ['as', 'b', 'abb', 'sss', 'ytr65', '', 'qw', 'a', 'b'],
+                     [6, 6, 2, 1, 3, np.inf, np.nan, np.nan, np.nan],
+                     [3., 5.3, np.nan, np.nan, np.inf, np.inf, 4.4, 3.7, 8.9]
+                     ]
+
+        for input_data in data_test:
+            S = pd.Series(input_data)
+
+            result_ref = test_impl(S)
+            result = hpat_func(S)
+            pd.testing.assert_series_equal(result, result_ref)
+
+            hpat_func_param1 = hpat.jit(test_impl_param)
+
+            for param1 in [0, 3, 10]:
+                result_param1_ref = test_impl_param(S, param1)
+                result_param1 = hpat_func_param1(S, param1)
+                pd.testing.assert_series_equal(result_param1, result_param1_ref)
+
+    @unittest.skip("Broke another three tests")
+    def test_series_head_idx(self):
+        def test_impl(S):
+            return S.head()
+
+        def test_impl_param(S, n):
+            return S.head(n)
+
+        hpat_func = hpat.jit(test_impl)
+
+        data_test = [[6, 6, 2, 1, 3, 3, 2, 1, 2],
+                     [1.1, 0.3, 2.1, 1, 3, 0.3, 2.1, 1.1, 2.2],
+                     [6, 6.1, 2.2, 1, 3, 0, 2.2, 1, 2],
+                     ['as', 'b', 'abb', 'sss', 'ytr65', '', 'qw', 'a', 'b'],
+                     [6, 6, 2, 1, 3, np.inf, np.nan, np.nan, np.nan],
+                     [3., 5.3, np.nan, np.nan, np.inf, np.inf, 4.4, 3.7, 8.9]
+                     ]
+
+        for input_data in data_test:
+            for index_data in data_test:
+                S = pd.Series(input_data, index_data)
+
+                result_ref = test_impl(S)
+                result = hpat_func(S)
+                pd.testing.assert_series_equal(result, result_ref)
+
+                hpat_func_param1 = hpat.jit(test_impl_param)
+
+                for param1 in [1, 3, 7]:
+                    result_param1_ref = test_impl_param(S, param1)
+                    result_param1 = hpat_func_param1(S, param1)
+                    pd.testing.assert_series_equal(result_param1, result_param1_ref)
+
     def test_series_median1(self):
         '''Verifies median implementation for float and integer series of random data'''
         def test_impl(S):