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cleanups
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4 files changed

+261
-238
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‎.pre-commit-config.yaml

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Original file line numberDiff line numberDiff line change
@@ -78,6 +78,27 @@ repos:
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--linelength=88,
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'--filter=-readability/casting,-runtime/int,-build/include_subdir,-readability/fn_size'
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]
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- repo: https://github.com/pycqa/pylint
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rev: v2.16.2
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hooks:
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- id: pylint
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stages: [manual]
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- repo: https://github.com/pycqa/pylint
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rev: v2.16.2
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hooks:
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- id: pylint
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alias: redefined-outer-name
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name: Redefining name from outer scope
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files: ^pandas/
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exclude: |
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(?x)
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^pandas/tests # keep excluded
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|/_testing/ # keep excluded
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|^pandas/util/_test_decorators\.py # keep excluded
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|^pandas/_version\.py # keep excluded
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|^pandas/conftest\.py # keep excluded
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args: [--disable=all, --enable=redefined-outer-name]
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stages: [manual]
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- repo: https://github.com/PyCQA/isort
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rev: 5.12.0
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hooks:

‎pandas/core/arrays/categorical.py

+1
Original file line numberDiff line numberDiff line change
@@ -1284,6 +1284,7 @@ def map(self, mapper, na_action: Literal["ignore"] | None = "ignore"):
12841284

12851285
if np.any(self._codes == -1):
12861286
new_categories = new_categories.insert(len(new_categories), np.nan)
1287+
12871288
return np.take(new_categories, self._codes)
12881289

12891290
__eq__ = _cat_compare_op(operator.eq)

‎pandas/tests/arrays/categorical/test_map.py

+112-113
Original file line numberDiff line numberDiff line change
@@ -15,124 +15,123 @@ def na_action(request):
1515
return request.param
1616

1717

18-
class TestMap:
19-
@pytest.mark.parametrize(
20-
"data, categories",
21-
[
22-
(list("abcbca"), list("cab")),
23-
(pd.interval_range(0, 3).repeat(3), pd.interval_range(0, 3)),
24-
],
25-
ids=["string", "interval"],
18+
@pytest.mark.parametrize(
19+
"data, categories",
20+
[
21+
(list("abcbca"), list("cab")),
22+
(pd.interval_range(0, 3).repeat(3), pd.interval_range(0, 3)),
23+
],
24+
ids=["string", "interval"],
25+
)
26+
def test_map_str(data, categories, ordered, na_action):
27+
# GH 31202 - override base class since we want to maintain categorical/ordered
28+
cat = Categorical(data, categories=categories, ordered=ordered)
29+
result = cat.map(str, na_action=na_action)
30+
expected = Categorical(
31+
map(str, data), categories=map(str, categories), ordered=ordered
2632
)
27-
def test_map_str(self, data, categories, ordered, na_action):
28-
# GH 31202 - override base class since we want to maintain categorical/ordered
29-
cat = Categorical(data, categories=categories, ordered=ordered)
30-
result = cat.map(str, na_action=na_action)
31-
expected = Categorical(
32-
map(str, data), categories=map(str, categories), ordered=ordered
33-
)
33+
tm.assert_categorical_equal(result, expected)
34+
35+
def test_map(na_action):
36+
cat = Categorical(list("ABABC"), categories=list("CBA"), ordered=True)
37+
result = cat.map(lambda x: x.lower(), na_action=na_action)
38+
exp = Categorical(list("ababc"), categories=list("cba"), ordered=True)
39+
tm.assert_categorical_equal(result, exp)
40+
41+
cat = Categorical(list("ABABC"), categories=list("BAC"), ordered=False)
42+
result = cat.map(lambda x: x.lower(), na_action=na_action)
43+
exp = Categorical(list("ababc"), categories=list("bac"), ordered=False)
44+
tm.assert_categorical_equal(result, exp)
45+
46+
# GH 12766: Return an index not an array
47+
result = cat.map(lambda x: 1, na_action=na_action)
48+
exp = Index(np.array([1] * 5, dtype=np.int64))
49+
tm.assert_index_equal(result, exp)
50+
51+
# change categories dtype
52+
cat = Categorical(list("ABABC"), categories=list("BAC"), ordered=False)
53+
54+
def f(x):
55+
return {"A": 10, "B": 20, "C": 30}.get(x)
56+
57+
result = cat.map(f, na_action=na_action)
58+
exp = Categorical([10, 20, 10, 20, 30], categories=[20, 10, 30], ordered=False)
59+
tm.assert_categorical_equal(result, exp)
60+
61+
mapper = Series([10, 20, 30], index=["A", "B", "C"])
62+
result = cat.map(mapper, na_action=na_action)
63+
tm.assert_categorical_equal(result, exp)
64+
65+
result = cat.map({"A": 10, "B": 20, "C": 30}, na_action=na_action)
66+
tm.assert_categorical_equal(result, exp)
67+
68+
@pytest.mark.parametrize(
69+
("data", "f", "expected"),
70+
(
71+
([1, 1, np.nan], pd.isna, Index([False, False, True])),
72+
([1, 2, np.nan], pd.isna, Index([False, False, True])),
73+
([1, 1, np.nan], {1: False}, Categorical([False, False, np.nan])),
74+
([1, 2, np.nan], {1: False, 2: False}, Index([False, False, np.nan])),
75+
(
76+
[1, 1, np.nan],
77+
Series([False, False]),
78+
Categorical([False, False, np.nan]),
79+
),
80+
(
81+
[1, 2, np.nan],
82+
Series([False] * 3),
83+
Index([False, False, np.nan]),
84+
),
85+
),
86+
)
87+
def test_map_with_nan_none(data, f, expected): # GH 24241
88+
values = Categorical(data)
89+
result = values.map(f, na_action=None)
90+
if isinstance(expected, Categorical):
3491
tm.assert_categorical_equal(result, expected)
35-
36-
def test_map(self, na_action):
37-
cat = Categorical(list("ABABC"), categories=list("CBA"), ordered=True)
38-
result = cat.map(lambda x: x.lower(), na_action=na_action)
39-
exp = Categorical(list("ababc"), categories=list("cba"), ordered=True)
40-
tm.assert_categorical_equal(result, exp)
41-
42-
cat = Categorical(list("ABABC"), categories=list("BAC"), ordered=False)
43-
result = cat.map(lambda x: x.lower(), na_action=na_action)
44-
exp = Categorical(list("ababc"), categories=list("bac"), ordered=False)
45-
tm.assert_categorical_equal(result, exp)
46-
47-
# GH 12766: Return an index not an array
48-
result = cat.map(lambda x: 1, na_action=na_action)
49-
exp = Index(np.array([1] * 5, dtype=np.int64))
50-
tm.assert_index_equal(result, exp)
51-
52-
# change categories dtype
53-
cat = Categorical(list("ABABC"), categories=list("BAC"), ordered=False)
54-
55-
def f(x):
56-
return {"A": 10, "B": 20, "C": 30}.get(x)
57-
58-
result = cat.map(f, na_action=na_action)
59-
exp = Categorical([10, 20, 10, 20, 30], categories=[20, 10, 30], ordered=False)
60-
tm.assert_categorical_equal(result, exp)
61-
62-
mapper = Series([10, 20, 30], index=["A", "B", "C"])
63-
result = cat.map(mapper, na_action=na_action)
64-
tm.assert_categorical_equal(result, exp)
65-
66-
result = cat.map({"A": 10, "B": 20, "C": 30}, na_action=na_action)
67-
tm.assert_categorical_equal(result, exp)
68-
69-
@pytest.mark.parametrize(
70-
("data", "f", "expected"),
92+
else:
93+
tm.assert_index_equal(result, expected)
94+
95+
@pytest.mark.parametrize(
96+
("data", "f", "expected"),
97+
(
98+
([1, 1, np.nan], pd.isna, Categorical([False, False, np.nan])),
99+
([1, 2, np.nan], pd.isna, Index([False, False, np.nan])),
100+
([1, 1, np.nan], {1: False}, Categorical([False, False, np.nan])),
101+
([1, 2, np.nan], {1: False, 2: False}, Index([False, False, np.nan])),
71102
(
72-
([1, 1, np.nan], pd.isna, Index([False, False, True])),
73-
([1, 2, np.nan], pd.isna, Index([False, False, True])),
74-
([1, 1, np.nan], {1: False}, Categorical([False, False, np.nan])),
75-
([1, 2, np.nan], {1: False, 2: False}, Index([False, False, np.nan])),
76-
(
77-
[1, 1, np.nan],
78-
Series([False, False]),
79-
Categorical([False, False, np.nan]),
80-
),
81-
(
82-
[1, 2, np.nan],
83-
Series([False] * 3),
84-
Index([False, False, np.nan]),
85-
),
103+
[1, 1, np.nan],
104+
Series([False, False]),
105+
Categorical([False, False, np.nan]),
86106
),
87-
)
88-
def test_map_with_nan_none(self, data, f, expected): # GH 24241
89-
values = Categorical(data)
90-
result = values.map(f, na_action=None)
91-
if isinstance(expected, Categorical):
92-
tm.assert_categorical_equal(result, expected)
93-
else:
94-
tm.assert_index_equal(result, expected)
95-
96-
@pytest.mark.parametrize(
97-
("data", "f", "expected"),
98107
(
99-
([1, 1, np.nan], pd.isna, Categorical([False, False, np.nan])),
100-
([1, 2, np.nan], pd.isna, Index([False, False, np.nan])),
101-
([1, 1, np.nan], {1: False}, Categorical([False, False, np.nan])),
102-
([1, 2, np.nan], {1: False, 2: False}, Index([False, False, np.nan])),
103-
(
104-
[1, 1, np.nan],
105-
Series([False, False]),
106-
Categorical([False, False, np.nan]),
107-
),
108-
(
109-
[1, 2, np.nan],
110-
Series([False, False, False]),
111-
Index([False, False, np.nan]),
112-
),
108+
[1, 2, np.nan],
109+
Series([False, False, False]),
110+
Index([False, False, np.nan]),
113111
),
114-
)
115-
def test_map_with_nan_ignore(self, data, f, expected): # GH 24241
116-
values = Categorical(data)
117-
result = values.map(f, na_action="ignore")
118-
if data[1] == 1:
119-
tm.assert_categorical_equal(result, expected)
120-
else:
121-
tm.assert_index_equal(result, expected)
122-
123-
def test_map_with_dict_or_series(self, na_action):
124-
orig_values = ["a", "B", 1, "a"]
125-
new_values = ["one", 2, 3.0, "one"]
126-
cat = Categorical(orig_values)
127-
128-
mapper = Series(new_values[:-1], index=orig_values[:-1])
129-
result = cat.map(mapper, na_action=na_action)
130-
131-
# Order of categories in result can be different
132-
expected = Categorical(new_values, categories=[3.0, 2, "one"])
112+
),
113+
)
114+
def test_map_with_nan_ignore(data, f, expected): # GH 24241
115+
values = Categorical(data)
116+
result = values.map(f, na_action="ignore")
117+
if data[1] == 1:
133118
tm.assert_categorical_equal(result, expected)
119+
else:
120+
tm.assert_index_equal(result, expected)
134121

135-
mapper = dict(zip(orig_values[:-1], new_values[:-1]))
136-
result = cat.map(mapper, na_action=na_action)
137-
# Order of categories in result can be different
138-
tm.assert_categorical_equal(result, expected)
122+
def test_map_with_dict_or_series(na_action):
123+
orig_values = ["a", "B", 1, "a"]
124+
new_values = ["one", 2, 3.0, "one"]
125+
cat = Categorical(orig_values)
126+
127+
mapper = Series(new_values[:-1], index=orig_values[:-1])
128+
result = cat.map(mapper, na_action=na_action)
129+
130+
# Order of categories in result can be different
131+
expected = Categorical(new_values, categories=[3.0, 2, "one"])
132+
tm.assert_categorical_equal(result, expected)
133+
134+
mapper = dict(zip(orig_values[:-1], new_values[:-1]))
135+
result = cat.map(mapper, na_action=na_action)
136+
# Order of categories in result can be different
137+
tm.assert_categorical_equal(result, expected)

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