def test_resample_panel_numpy(self): rng = date_range('1/1/2000', '6/30/2000') n = len(rng) panel = Panel(np.random.randn(3, n, 5), items=['one', 'two', 'three'], major_axis=rng, minor_axis=['a', 'b', 'c', 'd', 'e']) result = panel.resample('M', how=lambda x: x.mean(), axis=1) expected = panel.resample('M', how='mean', axis=1) tm.assert_panel_equal(result, expected)
def test_resample_panel_numpy(self): rng = date_range("1/1/2000", "6/30/2000") n = len(rng) panel = Panel( np.random.randn(3, n, 5), items=["one", "two", "three"], major_axis=rng, minor_axis=["a", "b", "c", "d", "e"], ) result = panel.resample("M", how=lambda x: x.mean(), axis=1) expected = panel.resample("M", how="mean", axis=1) tm.assert_panel_equal(result, expected)
def test_resample_panel(self): rng = date_range("1/1/2000", "6/30/2000") n = len(rng) panel = Panel( np.random.randn(3, n, 5), items=["one", "two", "three"], major_axis=rng, minor_axis=["a", "b", "c", "d", "e"], ) result = panel.resample("M", axis=1) def p_apply(panel, f): result = {} for item in panel.items: result[item] = f(panel[item]) return Panel(result, items=panel.items) expected = p_apply(panel, lambda x: x.resample("M")) tm.assert_panel_equal(result, expected) panel2 = panel.swapaxes(1, 2) result = panel2.resample("M", axis=2) expected = p_apply(panel2, lambda x: x.resample("M", axis=1)) tm.assert_panel_equal(result, expected)
def test_resample_panel(): rng = date_range('1/1/2000', '6/30/2000') n = len(rng) with catch_warnings(record=True): simplefilter("ignore", FutureWarning) panel = Panel(np.random.randn(3, n, 5), items=['one', 'two', 'three'], major_axis=rng, minor_axis=['a', 'b', 'c', 'd', 'e']) result = panel.resample('M', axis=1).mean() def p_apply(panel, f): result = {} for item in panel.items: result[item] = f(panel[item]) return Panel(result, items=panel.items) expected = p_apply(panel, lambda x: x.resample('M').mean()) tm.assert_panel_equal(result, expected) panel2 = panel.swapaxes(1, 2) result = panel2.resample('M', axis=2).mean() expected = p_apply(panel2, lambda x: x.resample('M', axis=1).mean()) tm.assert_panel_equal(result, expected)
def test_resample_panel_numpy(): rng = date_range('1/1/2000', '6/30/2000') n = len(rng) with catch_warnings(record=True): panel = Panel(np.random.randn(3, n, 5), items=['one', 'two', 'three'], major_axis=rng, minor_axis=['a', 'b', 'c', 'd', 'e']) result = panel.resample('M', axis=1).apply(lambda x: x.mean(1)) expected = panel.resample('M', axis=1).mean() tm.assert_panel_equal(result, expected) panel = panel.swapaxes(1, 2) result = panel.resample('M', axis=2).apply(lambda x: x.mean(2)) expected = panel.resample('M', axis=2).mean() tm.assert_panel_equal(result, expected)
def test_resample_panel(self): rng = date_range('1/1/2000', '6/30/2000') n = len(rng) panel = Panel(np.random.randn(3, n, 5), items=['one', 'two', 'three'], major_axis=rng, minor_axis=['a', 'b', 'c', 'd', 'e']) result = panel.resample('M', axis=1) def p_apply(panel, f): result = {} for item in panel.items: result[item] = f(panel[item]) return Panel(result, items=panel.items) expected = p_apply(panel, lambda x: x.resample('M')) tm.assert_panel_equal(result, expected) panel2 = panel.swapaxes(1, 2) result = panel2.resample('M', axis=2) expected = p_apply(panel2, lambda x: x.resample('M', axis=1)) tm.assert_panel_equal(result, expected)