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CLN: Consistent pandas.util.testing imports in pandas/tests/indexing #29291

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Oct 31, 2019
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CLN: Consistent pandas.util.testing imports in pandas/tests/indexing #29291

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85 changes: 42 additions & 43 deletions pandas/tests/indexing/test_categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,8 +15,7 @@
Timestamp,
)
from pandas.api.types import CategoricalDtype as CDT
from pandas.util import testing as tm
from pandas.util.testing import assert_frame_equal, assert_series_equal
import pandas.util.testing as tm


class TestCategoricalIndex:
Expand Down Expand Up @@ -52,7 +51,7 @@ def test_loc_scalar(self):
expected = DataFrame(
{"A": [0, 1, 5], "B": (Series(list("aaa")).astype(CDT(list("cab"))))}
).set_index("B")
assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

df = self.df.copy()
df.loc["a"] = 20
Expand All @@ -62,7 +61,7 @@ def test_loc_scalar(self):
"B": (Series(list("aabbca")).astype(CDT(list("cab")))),
}
).set_index("B")
assert_frame_equal(df, expected)
tm.assert_frame_equal(df, expected)

# value not in the categories
with pytest.raises(KeyError, match=r"^'d'$"):
Expand Down Expand Up @@ -329,12 +328,12 @@ def test_loc_listlike(self):
# list of labels
result = self.df.loc[["c", "a"]]
expected = self.df.iloc[[4, 0, 1, 5]]
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

result = self.df2.loc[["a", "b", "e"]]
exp_index = CategoricalIndex(list("aaabbe"), categories=list("cabe"), name="B")
expected = DataFrame({"A": [0, 1, 5, 2, 3, np.nan]}, index=exp_index)
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

# element in the categories but not in the values
with pytest.raises(KeyError, match=r"^'e'$"):
Expand All @@ -346,13 +345,13 @@ def test_loc_listlike(self):
result = df.loc[["a", "b", "e"]]
exp_index = CategoricalIndex(list("aaabbe"), categories=list("cabe"), name="B")
expected = DataFrame({"A": [0, 1, 5, 2, 3, 20]}, index=exp_index)
assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

df = self.df2.copy()
result = df.loc[["a", "b", "e"]]
exp_index = CategoricalIndex(list("aaabbe"), categories=list("cabe"), name="B")
expected = DataFrame({"A": [0, 1, 5, 2, 3, np.nan]}, index=exp_index)
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

# not all labels in the categories
with pytest.raises(
Expand Down Expand Up @@ -474,7 +473,7 @@ def test_getitem_with_listlike(self):
)
dummies = pd.get_dummies(cats)
result = dummies[[c for c in dummies.columns]]
assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

def test_setitem_listlike(self):

Expand All @@ -500,18 +499,18 @@ def test_ix_categorical_index(self):
cdf.columns = CategoricalIndex(df.columns)

expect = Series(df.loc["A", :], index=cdf.columns, name="A")
assert_series_equal(cdf.loc["A", :], expect)
tm.assert_series_equal(cdf.loc["A", :], expect)

expect = Series(df.loc[:, "X"], index=cdf.index, name="X")
assert_series_equal(cdf.loc[:, "X"], expect)
tm.assert_series_equal(cdf.loc[:, "X"], expect)

exp_index = CategoricalIndex(list("AB"), categories=["A", "B", "C"])
expect = DataFrame(df.loc[["A", "B"], :], columns=cdf.columns, index=exp_index)
assert_frame_equal(cdf.loc[["A", "B"], :], expect)
tm.assert_frame_equal(cdf.loc[["A", "B"], :], expect)

exp_columns = CategoricalIndex(list("XY"), categories=["X", "Y", "Z"])
expect = DataFrame(df.loc[:, ["X", "Y"]], index=cdf.index, columns=exp_columns)
assert_frame_equal(cdf.loc[:, ["X", "Y"]], expect)
tm.assert_frame_equal(cdf.loc[:, ["X", "Y"]], expect)

# non-unique
df = DataFrame(np.random.randn(3, 3), index=list("ABA"), columns=list("XYX"))
Expand All @@ -521,25 +520,25 @@ def test_ix_categorical_index(self):

exp_index = CategoricalIndex(list("AA"), categories=["A", "B"])
expect = DataFrame(df.loc["A", :], columns=cdf.columns, index=exp_index)
assert_frame_equal(cdf.loc["A", :], expect)
tm.assert_frame_equal(cdf.loc["A", :], expect)

exp_columns = CategoricalIndex(list("XX"), categories=["X", "Y"])
expect = DataFrame(df.loc[:, "X"], index=cdf.index, columns=exp_columns)
assert_frame_equal(cdf.loc[:, "X"], expect)
tm.assert_frame_equal(cdf.loc[:, "X"], expect)

expect = DataFrame(
df.loc[["A", "B"], :],
columns=cdf.columns,
index=CategoricalIndex(list("AAB")),
)
assert_frame_equal(cdf.loc[["A", "B"], :], expect)
tm.assert_frame_equal(cdf.loc[["A", "B"], :], expect)

expect = DataFrame(
df.loc[:, ["X", "Y"]],
index=cdf.index,
columns=CategoricalIndex(list("XXY")),
)
assert_frame_equal(cdf.loc[:, ["X", "Y"]], expect)
tm.assert_frame_equal(cdf.loc[:, ["X", "Y"]], expect)

def test_read_only_source(self):
# GH 10043
Expand All @@ -550,15 +549,15 @@ def test_read_only_source(self):
ro_array.setflags(write=False)
ro_df = DataFrame(ro_array)

assert_frame_equal(rw_df.iloc[[1, 2, 3]], ro_df.iloc[[1, 2, 3]])
assert_frame_equal(rw_df.iloc[[1]], ro_df.iloc[[1]])
assert_series_equal(rw_df.iloc[1], ro_df.iloc[1])
assert_frame_equal(rw_df.iloc[1:3], ro_df.iloc[1:3])
tm.assert_frame_equal(rw_df.iloc[[1, 2, 3]], ro_df.iloc[[1, 2, 3]])
tm.assert_frame_equal(rw_df.iloc[[1]], ro_df.iloc[[1]])
tm.assert_series_equal(rw_df.iloc[1], ro_df.iloc[1])
tm.assert_frame_equal(rw_df.iloc[1:3], ro_df.iloc[1:3])

assert_frame_equal(rw_df.loc[[1, 2, 3]], ro_df.loc[[1, 2, 3]])
assert_frame_equal(rw_df.loc[[1]], ro_df.loc[[1]])
assert_series_equal(rw_df.loc[1], ro_df.loc[1])
assert_frame_equal(rw_df.loc[1:3], ro_df.loc[1:3])
tm.assert_frame_equal(rw_df.loc[[1, 2, 3]], ro_df.loc[[1, 2, 3]])
tm.assert_frame_equal(rw_df.loc[[1]], ro_df.loc[[1]])
tm.assert_series_equal(rw_df.loc[1], ro_df.loc[1])
tm.assert_frame_equal(rw_df.loc[1:3], ro_df.loc[1:3])

def test_reindexing(self):
df = DataFrame(
Expand All @@ -574,19 +573,19 @@ def test_reindexing(self):
expected = DataFrame({"A": [0, 1, np.nan], "B": Series(list("abe"))}).set_index(
"B"
)
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

result = df.reindex(["a", "b"])
expected = DataFrame({"A": [0, 1], "B": Series(list("ab"))}).set_index("B")
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

result = df.reindex(["e"])
expected = DataFrame({"A": [np.nan], "B": Series(["e"])}).set_index("B")
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

result = df.reindex(["d"])
expected = DataFrame({"A": [np.nan], "B": Series(["d"])}).set_index("B")
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

# since we are actually reindexing with a Categorical
# then return a Categorical
Expand All @@ -596,40 +595,40 @@ def test_reindexing(self):
expected = DataFrame(
{"A": [0, np.nan], "B": Series(list("ae")).astype(CDT(cats))}
).set_index("B")
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

result = df.reindex(Categorical(["a"], categories=cats))
expected = DataFrame(
{"A": [0], "B": Series(list("a")).astype(CDT(cats))}
).set_index("B")
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

result = df.reindex(["a", "b", "e"])
expected = DataFrame({"A": [0, 1, np.nan], "B": Series(list("abe"))}).set_index(
"B"
)
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

result = df.reindex(["a", "b"])
expected = DataFrame({"A": [0, 1], "B": Series(list("ab"))}).set_index("B")
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

result = df.reindex(["e"])
expected = DataFrame({"A": [np.nan], "B": Series(["e"])}).set_index("B")
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

# give back the type of categorical that we received
result = df.reindex(Categorical(["a", "e"], categories=cats, ordered=True))
expected = DataFrame(
{"A": [0, np.nan], "B": Series(list("ae")).astype(CDT(cats, ordered=True))}
).set_index("B")
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

result = df.reindex(Categorical(["a", "d"], categories=["a", "d"]))
expected = DataFrame(
{"A": [0, np.nan], "B": Series(list("ad")).astype(CDT(["a", "d"]))}
).set_index("B")
assert_frame_equal(result, expected, check_index_type=True)
tm.assert_frame_equal(result, expected, check_index_type=True)

# passed duplicate indexers are not allowed
msg = "cannot reindex from a duplicate axis"
Expand Down Expand Up @@ -661,7 +660,7 @@ def test_loc_slice(self):

# result = df.loc[1:5]
# expected = df.iloc[[1,2,3,4]]
# assert_frame_equal(result, expected)
# tm.assert_frame_equal(result, expected)

def test_loc_and_at_with_categorical_index(self):
# GH 20629
Expand All @@ -681,19 +680,19 @@ def test_boolean_selection(self):

result = df3[df3.index == "a"]
expected = df3.iloc[[]]
assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

result = df4[df4.index == "a"]
expected = df4.iloc[[]]
assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

result = df3[df3.index == 1]
expected = df3.iloc[[0, 1, 3]]
assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

result = df4[df4.index == 1]
expected = df4.iloc[[0, 1, 3]]
assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

# since we have an ordered categorical

Expand All @@ -703,11 +702,11 @@ def test_boolean_selection(self):
# name='B')
result = df3[df3.index < 2]
expected = df3.iloc[[4]]
assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

result = df3[df3.index > 1]
expected = df3.iloc[[]]
assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

# unordered
# cannot be compared
Expand Down
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