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TST: refactored test_factorize (#32311) #82

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Mar 7, 2020
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TST: refactored test_factorize (#32311) #82

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73 changes: 17 additions & 56 deletions pandas/tests/base/test_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -547,66 +547,27 @@ def test_value_counts_datetime64(self, index_or_series):
result2 = td2.value_counts()
tm.assert_series_equal(result2, expected_s)

def test_factorize(self):
for orig in self.objs:
o = orig.copy()

if isinstance(o, Index) and o.is_boolean():
exp_arr = np.array([0, 1] + [0] * 8, dtype=np.intp)
exp_uniques = o
exp_uniques = Index([False, True])
else:
exp_arr = np.array(range(len(o)), dtype=np.intp)
exp_uniques = o
codes, uniques = o.factorize()

tm.assert_numpy_array_equal(codes, exp_arr)
if isinstance(o, Series):
tm.assert_index_equal(uniques, Index(orig), check_names=False)
else:
# factorize explicitly resets name
tm.assert_index_equal(uniques, exp_uniques, check_names=False)

def test_factorize_repeated(self):
for orig in self.objs:
o = orig.copy()
@pytest.mark.parametrize("sort", [True, False])
def test_factorize(self, index_or_series_obj, sort):
obj = index_or_series_obj
result_codes, result_uniques = obj.factorize(sort=sort)

# don't test boolean
if isinstance(o, Index) and o.is_boolean():
continue
constructor = pd.Index
if isinstance(obj, pd.MultiIndex):
constructor = pd.MultiIndex.from_tuples
expected_uniques = constructor(obj.unique())

# sort by value, and create duplicates
if isinstance(o, Series):
o = o.sort_values()
n = o.iloc[5:].append(o)
else:
indexer = o.argsort()
o = o.take(indexer)
n = o[5:].append(o)

exp_arr = np.array(
[5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=np.intp
)
codes, uniques = n.factorize(sort=True)

tm.assert_numpy_array_equal(codes, exp_arr)
if isinstance(o, Series):
tm.assert_index_equal(
uniques, Index(orig).sort_values(), check_names=False
)
else:
tm.assert_index_equal(uniques, o, check_names=False)
if sort:
expected_uniques = expected_uniques.sort_values()

exp_arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4], np.intp)
codes, uniques = n.factorize(sort=False)
tm.assert_numpy_array_equal(codes, exp_arr)
# construct an integer ndarray so that
# `expected_uniques.take(expected_codes)` is equal to `obj`
expected_uniques_list = list(expected_uniques)
expected_codes = [expected_uniques_list.index(val) for val in obj]
expected_codes = np.asarray(expected_codes, dtype=np.intp)

if isinstance(o, Series):
expected = Index(o.iloc[5:10].append(o.iloc[:5]))
tm.assert_index_equal(uniques, expected, check_names=False)
else:
expected = o[5:10].append(o[:5])
tm.assert_index_equal(uniques, expected, check_names=False)
tm.assert_numpy_array_equal(result_codes, expected_codes)
tm.assert_index_equal(result_uniques, expected_uniques)

def test_duplicated_drop_duplicates_index(self):
# GH 4060
Expand Down