def test_index_properties_dtype(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
self.assertEqual(pi.dtype, oi.dtype)
pi = pd.Index([1.0, 2, 3])
oi = pd.Index([1.0, 2, 3])
self.assertEqual(pi.dtype, oi.dtype)
pi = pd.Index(['a', 'b'], dtype=str)
oi = pd.Index(['a', 'b'], dtype=str)
self.assertEqual(pi.dtype, oi.dtype)
pi = pd.Index([pd.to_datetime('1/1/2018'), pd.to_datetime('2/1/2018')])
oi = pd.Index([pd.to_datetime('1/1/2018'), pd.to_datetime('2/1/2018')])
self.assertEqual(pi.dtype, oi.dtype)
# dtype.str
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
self.assertEqual(pi.dtype.str, oi.dtype.str)
pi = pd.Index([1.0, 2, 3])
oi = pd.Index([1.0, 2, 3])
self.assertEqual(pi.dtype.str, oi.dtype.str)
pi = pd.Index(['a', 'b'], dtype=str)
oi = pd.Index(['a', 'b'], dtype=str)
self.assertEqual(pi.dtype.str, oi.dtype.str)
pi = pd.Index([pd.to_datetime('1/1/2018'), pd.to_datetime('2/1/2018')])
oi = pd.Index([pd.to_datetime('1/1/2018'), pd.to_datetime('2/1/2018')])
self.assertEqual(pi.dtype.str, oi.dtype.str)
def test_index_properties_has_duplicates(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
# TODO：NOT IMPLEMENTED
# self.assertEqual(pi.has_duplicates, oi.has_duplicates)
pi = pd.Index([1, 1, 1])
oi = orca.Index([1, 1, 1])
def test_index_properties_is_hasnans(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
self.assertEqual(pi.hasnans, oi.hasnans)
pi = pd.Index([1, np.nan, 1])
oi = orca.Index([1, np.nan, 1])
self.assertEqual(pi.hasnans, oi.hasnans)
def test_index_properties_is_unique(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
# FIXME：BUG
# self.assertEqual(pi.is_unique, oi.is_unique)
pi = pd.Index([1, 1, 1])
oi = orca.Index([1, 1, 1])
def test_index_properties_inferred_type(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
# TODO：NOT IMPLEMENTED
# self.assertEqual(pi.inferred_type, oi.inferred_type)
pi = pd.Index([1.0, 2, 3])
oi = orca.Index([1.0, 2, 3])
# self.assertEqual(pi.inferred_type, oi.inferred_type)
pi = pd.Index(['a', 'b'], dtype=str)
oi = orca.Index(['a', 'b'], dtype=str)
# self.assertEqual(pi.inferred_type, oi.inferred_type)
pi = pd.Index([pd.to_datetime('1/1/2018'), pd.to_datetime('2/1/2018')])
oi = orca.Index([pd.to_datetime('1/1/2018'), pd.to_datetime('2/1/2018')])
def test_index_properties_is_all_dates(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
self.assertEqual(pi.is_all_dates, oi.is_all_dates)
pi = pd.Index([1.0, 2, 3])
oi = pd.Index([1.0, 2, 3])
self.assertEqual(pi.is_all_dates, oi.is_all_dates)
pi = pd.Index(['a', 'b'], dtype=str)
oi = pd.Index(['a', 'b'], dtype=str)
self.assertEqual(pi.is_all_dates, oi.is_all_dates)
pi = pd.Index([pd.to_datetime('1/1/2018'), pd.to_datetime('2/1/2018')])
oi = pd.Index([pd.to_datetime('1/1/2018'), pd.to_datetime('2/1/2018')])
self.assertEqual(pi.is_all_dates, oi.is_all_dates)
def test_index_properties_is_monotonic_decreasing(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
self.assertEqual(pi.is_monotonic_decreasing, oi.is_monotonic_decreasing)
def test_index_properties_memory_usage(self):
pi = pd.Index([1, 2, 3], name=['a', 'b', 'c'])
oi = orca.Index([1, 2, 3], name=['a', 'b', 'c'])
def test_index_properties_T(self):
pi = pd.Index([1, 2, 3], name='a')
oi = orca.Index([1, 2, 3], name='a')
assert_index_equal(pi.T, oi.T.to_pandas())
def test_index_properties_empty(self):
pi = pd.Index([1, 2, 3], name=['a', 'b', 'c'])
oi = orca.Index([1, 2, 3], name=['a', 'b', 'c'])
def test_index_properties_values(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
self.assertEqual(repr(pi.values), repr(oi.values))
def test_index_properties_size(self):
pi = pd.Index([1, 2, 3], name=['a', 'b', 'c'])
oi = orca.Index([1, 2, 3], name=['a', 'b', 'c'])
self.assertEqual(pi.size, oi.size)
def test_index_properties_shape(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
self.assertEqual(pi.shape, oi.shape)
def test_index(self):
pi = pd.Index([1, 2, 3])
oi = orca.Index([1, 2, 3])
assert_index_equal(pi, oi.to_pandas())