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():
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_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)
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)
