def test_int_index(self): from pandas.core.series import Series arr = np.random.randn(100, 4) result = lib.reduce(arr, np.sum, labels=Index(np.arange(4))) expected = arr.sum(0) assert_almost_equal(result, expected) result = lib.reduce(arr, np.sum, axis=1, labels=Index(np.arange(100))) expected = arr.sum(1) assert_almost_equal(result, expected) dummy = Series(0., index=np.arange(100)) result = lib.reduce(arr, np.sum, dummy=dummy, labels=Index(np.arange(4))) expected = arr.sum(0) assert_almost_equal(result, expected) dummy = Series(0., index=np.arange(4)) result = lib.reduce(arr, np.sum, axis=1, dummy=dummy, labels=Index(np.arange(100))) expected = arr.sum(1) assert_almost_equal(result, expected) result = lib.reduce(arr, np.sum, axis=1, dummy=dummy, labels=Index(np.arange(100))) assert_almost_equal(result, expected)
def test_int_index(self): from pandas.core.series import Series arr = np.random.randn(100, 4) result = lib.reduce(arr, np.sum, labels=Index(np.arange(4))) expected = arr.sum(0) assert_almost_equal(result, expected) result = lib.reduce(arr, np.sum, axis=1, labels=Index(np.arange(100))) expected = arr.sum(1) assert_almost_equal(result, expected) dummy = Series(0., index=np.arange(100)) result = lib.reduce(arr, np.sum, dummy=dummy, labels=Index(np.arange(4))) expected = arr.sum(0) assert_almost_equal(result, expected) dummy = Series(0., index=np.arange(4)) result = lib.reduce(arr, np.sum, axis=1, dummy=dummy, labels=Index(np.arange(100))) expected = arr.sum(1) assert_almost_equal(result, expected) result = lib.reduce(arr, np.sum, axis=1, dummy=dummy, labels=Index(np.arange(100))) assert_almost_equal(result, expected)
def apply_raw(self): try: result = lib.reduce(self.values, self.f, axis=self.axis) except Exception: result = np.apply_along_axis(self.f, self.axis, self.values) # TODO: mixed type case from pandas import DataFrame, Series if result.ndim == 2: return DataFrame(result, index=self.index, columns=self.columns) else: return Series(result, index=self.agg_axis)
def apply_raw(self): try: result = lib.reduce(self.values, self.f, axis=self.axis) except Exception: result = np.apply_along_axis(self.f, self.axis, self.values) # TODO: mixed type case from pandas import DataFrame, Series if result.ndim == 2: return DataFrame(result, index=self.index, columns=self.columns) else: return Series(result, index=self.agg_axis)
def apply_standard(self): from pandas import Series reduce = self.reduce if reduce is None: reduce = True # try to reduce first (by default) # this only matters if the reduction in values is of different dtype # e.g. if we want to apply to a SparseFrame, then can't directly reduce if reduce: values = self.values # we cannot reduce using non-numpy dtypes, # as demonstrated in gh-12244 if not is_extension_type(values): # Create a dummy Series from an empty array index = self.obj._get_axis(self.axis) empty_arr = np.empty(len(index), dtype=values.dtype) dummy = Series(empty_arr, index=index, dtype=values.dtype) try: labels = self.agg_axis result = lib.reduce(values, self.f, axis=self.axis, dummy=dummy, labels=labels) return Series(result, index=labels) except Exception: pass # compute the result using the series generator results, res_index, res_columns = self._apply_series_generator() # wrap results return self.wrap_results(results, res_index, res_columns)
def apply_standard(self): from pandas import Series reduce = self.reduce if reduce is None: reduce = True # try to reduce first (by default) # this only matters if the reduction in values is of different dtype # e.g. if we want to apply to a SparseFrame, then can't directly reduce if reduce: values = self.values # we cannot reduce using non-numpy dtypes, # as demonstrated in gh-12244 if not is_extension_type(values): # Create a dummy Series from an empty array index = self.obj._get_axis(self.axis) empty_arr = np.empty(len(index), dtype=values.dtype) dummy = Series(empty_arr, index=index, dtype=values.dtype) try: labels = self.agg_axis result = lib.reduce(values, self.f, axis=self.axis, dummy=dummy, labels=labels) return Series(result, index=labels) except Exception: pass # compute the result using the series generator results, res_index, res_columns = self._apply_series_generator() # wrap results return self.wrap_results(results, res_index, res_columns)