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Oct 7, 2021
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TST/REF: collect/de-dup index tests #43914

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64dd6f5
TST/REF: collect/de-dup index tests
jbrockmendel Oct 7, 2021
729935e
typo fixup
jbrockmendel Oct 7, 2021
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32 changes: 32 additions & 0 deletions pandas/tests/frame/methods/test_reindex.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1078,3 +1078,35 @@ def test_reindex_datetimelike_to_object(self, dtype):
assert res.iloc[-1, 0] is fv
assert res.iloc[-1, 1] is fv
tm.assert_frame_equal(res, expected)

@pytest.mark.parametrize(
"index_df,index_res,index_exp",
[
(
CategoricalIndex([], categories=["A"]),
Index(["A"]),
Index(["A"]),
),
(
CategoricalIndex([], categories=["A"]),
Index(["B"]),
Index(["B"]),
),
(
CategoricalIndex([], categories=["A"]),
CategoricalIndex(["A"]),
CategoricalIndex(["A"]),
),
(
CategoricalIndex([], categories=["A"]),
CategoricalIndex(["B"]),
CategoricalIndex(["B"]),
),
],
)
def test_reindex_not_category(self, index_df, index_res, index_exp):
# GH#28690
df = DataFrame(index=index_df)
result = df.reindex(index=index_res)
expected = DataFrame(index=index_exp)
tm.assert_frame_equal(result, expected)
42 changes: 0 additions & 42 deletions pandas/tests/indexes/categorical/test_reindex.py
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Original file line number Diff line number Diff line change
@@ -1,13 +1,10 @@
import numpy as np
import pytest

from pandas import (
Categorical,
CategoricalIndex,
DataFrame,
Index,
Interval,
Series,
)
import pandas._testing as tm

Expand Down Expand Up @@ -66,45 +63,6 @@ def test_reindex_empty_index(self):
tm.assert_index_equal(res, Index(["a", "b"]), exact=True)
tm.assert_numpy_array_equal(indexer, np.array([-1, -1], dtype=np.intp))

def test_reindex_missing_category(self):
# GH: 18185
ser = Series([1, 2, 3, 1], dtype="category")
msg = r"Cannot setitem on a Categorical with a new category \(-1\)"
with pytest.raises(TypeError, match=msg):
ser.reindex([1, 2, 3, 4, 5], fill_value=-1)

@pytest.mark.parametrize(
"index_df,index_res,index_exp",
[
(
CategoricalIndex([], categories=["A"]),
Index(["A"]),
Index(["A"]),
),
(
CategoricalIndex([], categories=["A"]),
Index(["B"]),
Index(["B"]),
),
(
CategoricalIndex([], categories=["A"]),
CategoricalIndex(["A"]),
CategoricalIndex(["A"]),
),
(
CategoricalIndex([], categories=["A"]),
CategoricalIndex(["B"]),
CategoricalIndex(["B"]),
),
],
)
def test_reindex_not_category(self, index_df, index_res, index_exp):
# GH: 28690
df = DataFrame(index=index_df)
result = df.reindex(index=index_res)
expected = DataFrame(index=index_exp)
tm.assert_frame_equal(result, expected)

def test_reindex_categorical_added_category(self):
# GH 42424
ci = CategoricalIndex(
Expand Down
37 changes: 36 additions & 1 deletion pandas/tests/indexes/datetimes/test_date_range.py
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Original file line number Diff line number Diff line change
Expand Up @@ -121,6 +121,41 @@ def test_date_range_timestamp_equiv_preserve_frequency(self):


class TestDateRanges:
@pytest.mark.parametrize("freq", ["N", "U", "L", "T", "S", "H", "D"])
def test_date_range_edges(self, freq):
# GH#13672
td = Timedelta(f"1{freq}")
ts = Timestamp("1970-01-01")

idx = date_range(
start=ts + td,
end=ts + 4 * td,
freq=freq,
)
exp = DatetimeIndex(
[ts + n * td for n in range(1, 5)],
freq=freq,
)
tm.assert_index_equal(idx, exp)

# start after end
idx = date_range(
start=ts + 4 * td,
end=ts + td,
freq=freq,
)
exp = DatetimeIndex([], freq=freq)
tm.assert_index_equal(idx, exp)

# start matches end
idx = date_range(
start=ts + td,
end=ts + td,
freq=freq,
)
exp = DatetimeIndex([ts + td], freq=freq)
tm.assert_index_equal(idx, exp)

def test_date_range_near_implementation_bound(self):
# GH#???
freq = Timedelta(1)
Expand Down Expand Up @@ -717,7 +752,7 @@ def test_timezone_comparaison_bug(self):
result = date_range(start, periods=2, tz="US/Eastern")
assert len(result) == 2

def test_timezone_comparaison_assert(self):
def test_timezone_comparison_assert(self):
start = Timestamp("20130220 10:00", tz="US/Eastern")
msg = "Inferred time zone not equal to passed time zone"
with pytest.raises(AssertionError, match=msg):
Expand Down
136 changes: 0 additions & 136 deletions pandas/tests/indexes/datetimes/test_misc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,142 +19,6 @@
from pandas.core.arrays import DatetimeArray


class TestTimeSeries:
def test_range_edges(self):
# GH#13672
idx = date_range(
start=Timestamp("1970-01-01 00:00:00.000000001"),
end=Timestamp("1970-01-01 00:00:00.000000004"),
freq="N",
)
exp = DatetimeIndex(
[
"1970-01-01 00:00:00.000000001",
"1970-01-01 00:00:00.000000002",
"1970-01-01 00:00:00.000000003",
"1970-01-01 00:00:00.000000004",
],
freq="N",
)
tm.assert_index_equal(idx, exp)

def test_range_edges2(self):

idx = date_range(
start=Timestamp("1970-01-01 00:00:00.000000004"),
end=Timestamp("1970-01-01 00:00:00.000000001"),
freq="N",
)
exp = DatetimeIndex([], freq="N")
tm.assert_index_equal(idx, exp)

def test_range_edges3(self):

idx = date_range(
start=Timestamp("1970-01-01 00:00:00.000000001"),
end=Timestamp("1970-01-01 00:00:00.000000001"),
freq="N",
)
exp = DatetimeIndex(["1970-01-01 00:00:00.000000001"], freq="N")
tm.assert_index_equal(idx, exp)

def test_range_edges4(self):

idx = date_range(
start=Timestamp("1970-01-01 00:00:00.000001"),
end=Timestamp("1970-01-01 00:00:00.000004"),
freq="U",
)
exp = DatetimeIndex(
[
"1970-01-01 00:00:00.000001",
"1970-01-01 00:00:00.000002",
"1970-01-01 00:00:00.000003",
"1970-01-01 00:00:00.000004",
],
freq="U",
)
tm.assert_index_equal(idx, exp)

def test_range_edges5(self):

idx = date_range(
start=Timestamp("1970-01-01 00:00:00.001"),
end=Timestamp("1970-01-01 00:00:00.004"),
freq="L",
)
exp = DatetimeIndex(
[
"1970-01-01 00:00:00.001",
"1970-01-01 00:00:00.002",
"1970-01-01 00:00:00.003",
"1970-01-01 00:00:00.004",
],
freq="L",
)
tm.assert_index_equal(idx, exp)

def test_range_edges6(self):
idx = date_range(
start=Timestamp("1970-01-01 00:00:01"),
end=Timestamp("1970-01-01 00:00:04"),
freq="S",
)
exp = DatetimeIndex(
[
"1970-01-01 00:00:01",
"1970-01-01 00:00:02",
"1970-01-01 00:00:03",
"1970-01-01 00:00:04",
],
freq="S",
)
tm.assert_index_equal(idx, exp)

def test_range_edges7(self):
idx = date_range(
start=Timestamp("1970-01-01 00:01"),
end=Timestamp("1970-01-01 00:04"),
freq="T",
)
exp = DatetimeIndex(
[
"1970-01-01 00:01",
"1970-01-01 00:02",
"1970-01-01 00:03",
"1970-01-01 00:04",
],
freq="T",
)
tm.assert_index_equal(idx, exp)

def test_range_edges8(self):
idx = date_range(
start=Timestamp("1970-01-01 01:00"),
end=Timestamp("1970-01-01 04:00"),
freq="H",
)
exp = DatetimeIndex(
[
"1970-01-01 01:00",
"1970-01-01 02:00",
"1970-01-01 03:00",
"1970-01-01 04:00",
],
freq="H",
)
tm.assert_index_equal(idx, exp)

def test_range_edges9(self):
idx = date_range(
start=Timestamp("1970-01-01"), end=Timestamp("1970-01-04"), freq="D"
)
exp = DatetimeIndex(
["1970-01-01", "1970-01-02", "1970-01-03", "1970-01-04"], freq="D"
)
tm.assert_index_equal(idx, exp)


class TestDatetime64:
def test_no_millisecond_field(self):
msg = "type object 'DatetimeIndex' has no attribute 'millisecond'"
Expand Down
26 changes: 26 additions & 0 deletions pandas/tests/indexes/period/test_partial_slicing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@

from pandas import (
DataFrame,
PeriodIndex,
Series,
date_range,
period_range,
Expand All @@ -11,6 +12,31 @@


class TestPeriodIndex:
def test_getitem_periodindex_duplicates_string_slice(self):
# monotonic
idx = PeriodIndex([2000, 2007, 2007, 2009, 2009], freq="A-JUN")
ts = Series(np.random.randn(len(idx)), index=idx)

result = ts["2007"]
expected = ts[1:3]
tm.assert_series_equal(result, expected)
result[:] = 1
assert (ts[1:3] == 1).all()

# not monotonic
idx = PeriodIndex([2000, 2007, 2007, 2009, 2007], freq="A-JUN")
ts = Series(np.random.randn(len(idx)), index=idx)

result = ts["2007"]
expected = ts[idx == "2007"]
tm.assert_series_equal(result, expected)

def test_getitem_periodindex_quarter_string(self):
pi = PeriodIndex(["2Q05", "3Q05", "4Q05", "1Q06", "2Q06"], freq="Q")
ser = Series(np.random.rand(len(pi)), index=pi).cumsum()
# Todo: fix these accessors!
assert ser["05Q4"] == ser[2]

def test_pindex_slice_index(self):
pi = period_range(start="1/1/10", end="12/31/12", freq="M")
s = Series(np.random.rand(len(pi)), index=pi)
Expand Down
25 changes: 0 additions & 25 deletions pandas/tests/indexes/period/test_period.py
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Original file line number Diff line number Diff line change
Expand Up @@ -245,25 +245,6 @@ def test_is_(self):
assert not index.is_(index - 2)
assert not index.is_(index - 0)

def test_index_duplicate_periods(self):
# monotonic
idx = PeriodIndex([2000, 2007, 2007, 2009, 2009], freq="A-JUN")
ts = Series(np.random.randn(len(idx)), index=idx)

result = ts["2007"]
expected = ts[1:3]
tm.assert_series_equal(result, expected)
result[:] = 1
assert (ts[1:3] == 1).all()

# not monotonic
idx = PeriodIndex([2000, 2007, 2007, 2009, 2007], freq="A-JUN")
ts = Series(np.random.randn(len(idx)), index=idx)

result = ts["2007"]
expected = ts[idx == "2007"]
tm.assert_series_equal(result, expected)

def test_index_unique(self):
idx = PeriodIndex([2000, 2007, 2007, 2009, 2009], freq="A-JUN")
expected = PeriodIndex([2000, 2007, 2009], freq="A-JUN")
Expand Down Expand Up @@ -292,12 +273,6 @@ def test_pindex_fieldaccessor_nat(self):
exp = Index([1, 2, -1, 3, 4], dtype=np.int64, name="name")
tm.assert_index_equal(idx.month, exp)

def test_pindex_qaccess(self):
pi = PeriodIndex(["2Q05", "3Q05", "4Q05", "1Q06", "2Q06"], freq="Q")
s = Series(np.random.rand(len(pi)), index=pi).cumsum()
# Todo: fix these accessors!
assert s["05Q4"] == s[2]

def test_pindex_multiples(self):
expected = PeriodIndex(
["2011-01", "2011-03", "2011-05", "2011-07", "2011-09", "2011-11"],
Expand Down
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