def test_describe_cols(self):
test_list = [[1, 2],[2, 3],[3, 4],[4, 5],[5, 6],[6, 7]]
test_nd = np.array(test_list)
test_sa = np.array([(1, 2, 'a'), (2, 3, 'b'), (3, 4, 'c'), (4, 5, 'd'),
(5, 6, 'e'), (6, 7, 'f')],
dtype=[('id', int), ('val', float), ('name', 'S1')])
ctrl_list = np.array([('f0', 6, 3.5, 1.707825127659933, 1, 6),
('f1', 6, 4.5, 1.707825127659933, 2, 7)],
dtype=[('Column Name', 'S2'), ('Count', int),
('Mean', float), ('Standard Dev', float),
('Minimum', int), ('Maximum', int)])
ctrl_printout = """
Column Name Count Mean Standard Dev Minimum Maximum
0 f0 6 3.5 1.70782512766 1 6
1 f1 6 4.5 1.70782512766 2 7
""".strip()
with uft.rerout_stdout() as get_stdout:
self.assertTrue(uft.array_equal(ctrl_list,
describe_cols(
test_list)))
self.assertEqual(get_stdout().strip(), ctrl_printout)
self.assertTrue(uft.array_equal(ctrl_list,
describe_cols(
test_nd, verbose=False)))
ctrl_sa = np.array([('id', 6, 3.5, 1.707825127659933, 1, 6),
('val', 6, 4.5, 1.707825127659933, 2, 7),
('name', np.nan, np.nan, np.nan, np.nan, np.nan)],
dtype=[('Column Name', 'S4'), ('Count', float),
('Mean', float), ('Standard Dev', float),
('Minimum', float), ('Maximum', float)])
self.assertTrue(uft.array_equal(ctrl_sa,
describe_cols(
test_sa,
verbose=False)))
def test_describe_cols(self):
test_list = [[1, 2],[2, 3],[3, 4],[4, 5],[5, 6],[6, 7]]
test_nd = np.array(test_list)
test_sa = np.array([(1, 2, 'a'), (2, 3, 'b'), (3, 4, 'c'), (4, 5, 'd'),
(5, 6, 'e'), (6, 7, 'f')],
dtype=[('id', int), ('val', float), ('name', 'S1')])
ctrl_list = np.array([('f0', 6, 3.5, 1.707825127659933, 1, 6),
('f1', 6, 4.5, 1.707825127659933, 2, 7)],
dtype=[('Column Name', 'S2'), ('Count', int),
('Mean', float), ('Standard Dev', float),
('Minimum', int), ('Maximum', int)])
self.assertTrue(uft.array_equal(ctrl_list,
describe_cols(test_list)))
self.assertTrue(uft.array_equal(ctrl_list,
describe_cols(test_nd)))
ctrl_sa = np.array([('id', 6, 3.5, 1.707825127659933, 1, 6),
('val', 6, 4.5, 1.707825127659933, 2, 7),
('name', np.nan, np.nan, np.nan, np.nan, np.nan)],
dtype=[('Column Name', 'S4'), ('Count', float),
('Mean', float), ('Standard Dev', float),
('Minimum', float), ('Maximum', float)])
self.assertTrue(uft.array_equal(ctrl_sa,
describe_cols(test_sa)))
