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jbrockmendeljbrockmendel
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update tests
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10 files changed

+30
-51
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10 files changed

+30
-51
lines changed

‎pandas/tests/frame/methods/test_map.py

Lines changed: 4 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -159,14 +159,15 @@ def test_map_box():
159159
tm.assert_frame_equal(result, expected)
160160

161161

162-
def test_frame_map_dont_convert_datetime64():
163-
df = DataFrame({"x1": [datetime(1996, 1, 1)]})
162+
def test_frame_map_dont_convert_datetime64(unit):
163+
dtype = f"M8[{unit}]"
164+
df = DataFrame({"x1": [datetime(1996, 1, 1)]}, dtype=dtype)
164165

165166
df = df.map(lambda x: x + BDay())
166167
df = df.map(lambda x: x + BDay())
167168

168169
result = df.x1.dtype
169-
assert result == "M8[us]"
170+
assert result == dtype
170171

171172

172173
def test_map_function_runs_once():

‎pandas/tests/groupby/test_timegrouper.py

Lines changed: 11 additions & 24 deletions
Original file line numberDiff line numberDiff line change
@@ -46,7 +46,6 @@ def frame_for_truncated_bingrouper():
4646
],
4747
}
4848
)
49-
df["Date"] = df["Date"].astype("M8[ns]")
5049
return df
5150

5251

@@ -94,7 +93,6 @@ def test_groupby_with_timegrouper(self):
9493
],
9594
}
9695
)
97-
df_original["Date"] = df_original["Date"].astype("M8[ns]")
9896

9997
# GH 6908 change target column's order
10098
df_reordered = df_original.sort_values(by="Quantity")
@@ -185,7 +183,6 @@ def test_timegrouper_with_reg_groups(self):
185183
],
186184
}
187185
).set_index("Date")
188-
df_original.index = df_original.index.as_unit("ns")
189186

190187
df_sorted = df_original.sort_values(by="Quantity", ascending=False)
191188

@@ -200,9 +197,7 @@ def test_timegrouper_with_reg_groups(self):
200197
datetime(2013, 12, 31, 0, 0),
201198
],
202199
}
203-
)
204-
expected["Date"] = expected["Date"].astype("M8[ns]")
205-
expected = expected.set_index(["Date", "Buyer"])
200+
).set_index(["Date", "Buyer"])
206201

207202
msg = "The default value of numeric_only"
208203
result = df.groupby([Grouper(freq="YE"), "Buyer"]).sum(numeric_only=True)
@@ -219,9 +214,7 @@ def test_timegrouper_with_reg_groups(self):
219214
datetime(2013, 7, 1, 0, 0),
220215
],
221216
}
222-
)
223-
expected["Date"] = expected["Date"].astype("M8[ns]")
224-
expected = expected.set_index(["Date", "Buyer"])
217+
).set_index(["Date", "Buyer"])
225218
result = df.groupby([Grouper(freq="6MS"), "Buyer"]).sum(numeric_only=True)
226219
tm.assert_frame_equal(result, expected)
227220

@@ -241,9 +234,7 @@ def test_timegrouper_with_reg_groups(self):
241234
datetime(2013, 10, 2, 14, 0),
242235
],
243236
}
244-
)
245-
df_original["Date"] = df_original["Date"].astype("M8[ns]")
246-
df_original = df_original.set_index("Date")
237+
).set_index("Date")
247238

248239
df_sorted = df_original.sort_values(by="Quantity", ascending=False)
249240
for df in [df_original, df_sorted]:
@@ -259,9 +250,7 @@ def test_timegrouper_with_reg_groups(self):
259250
datetime(2013, 10, 2, 0, 0),
260251
],
261252
}
262-
)
263-
expected["Date"] = expected["Date"].astype("M8[ns]")
264-
expected = expected.set_index(["Date", "Buyer"])
253+
).set_index(["Date", "Buyer"])
265254

266255
result = df.groupby([Grouper(freq="1D"), "Buyer"]).sum(numeric_only=True)
267256
tm.assert_frame_equal(result, expected)
@@ -277,9 +266,7 @@ def test_timegrouper_with_reg_groups(self):
277266
datetime(2013, 10, 31, 0, 0),
278267
],
279268
}
280-
)
281-
expected["Date"] = expected["Date"].astype("M8[ns]")
282-
expected = expected.set_index(["Date", "Buyer"])
269+
).set_index(["Date", "Buyer"])
283270
tm.assert_frame_equal(result, expected)
284271

285272
# passing the name
@@ -322,9 +309,7 @@ def test_timegrouper_with_reg_groups(self):
322309
datetime(2013, 11, 30, 0, 0),
323310
],
324311
}
325-
)
326-
expected["Date"] = expected["Date"].astype("M8[ns]")
327-
expected = expected.set_index(["Date", "Buyer"])
312+
).set_index(["Date", "Buyer"])
328313
tm.assert_frame_equal(result, expected)
329314

330315
# error as we have both a level and a name!
@@ -340,7 +325,7 @@ def test_timegrouper_with_reg_groups(self):
340325
columns=["Quantity"],
341326
index=DatetimeIndex(
342327
[datetime(2013, 10, 31, 0, 0)], freq=offsets.MonthEnd(), name="Date"
343-
).as_unit("ns"),
328+
),
344329
)
345330
result = df.groupby(Grouper(freq="1ME")).sum(numeric_only=True)
346331
tm.assert_frame_equal(result, expected)
@@ -552,7 +537,9 @@ def test_groupby_groups_datetimeindex2(self):
552537
for date in dates:
553538
result = grouped.get_group(date)
554539
data = [[df.loc[date, "A"], df.loc[date, "B"]]]
555-
expected_index = DatetimeIndex([date], name="date", freq="D").as_unit("ns")
540+
expected_index = DatetimeIndex(
541+
[date], name="date", freq="D", dtype=index.dtype
542+
)
556543
expected = DataFrame(data, columns=list("AB"), index=expected_index)
557544
tm.assert_frame_equal(result, expected)
558545

@@ -587,7 +574,7 @@ def test_groupby_groups_datetimeindex_tz(self):
587574
],
588575
tz="US/Pacific",
589576
name="datetime",
590-
).as_unit("s")
577+
)
591578
exp_idx2 = Index(["a", "b"] * 3, name="label")
592579
exp_idx = MultiIndex.from_arrays([exp_idx1, exp_idx2])
593580
expected = DataFrame(

‎pandas/tests/groupby/transform/test_transform.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -108,7 +108,7 @@ def test_transform_fast2():
108108
{
109109
"grouping": [0, 1, 1, 3],
110110
"f": [1.1, 2.1, 3.1, 4.5],
111-
"d": date_range("2014-1-1", "2014-1-4", unit="s"),
111+
"d": date_range("2014-1-1", "2014-1-4"),
112112
"i": [1, 2, 3, 4],
113113
},
114114
columns=["grouping", "f", "i", "d"],

‎pandas/tests/indexes/datetimes/test_indexing.py

Lines changed: 1 addition & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -273,9 +273,8 @@ def test_take(self):
273273
["2011-01-29", "2011-01-03", "2011-01-06"],
274274
dtype=idx.dtype,
275275
freq=None,
276-
tz=idx.tz,
277276
name="idx",
278-
).as_unit("ns")
277+
)
279278
tm.assert_index_equal(result, expected)
280279
assert result.freq is None
281280

‎pandas/tests/indexes/datetimes/test_timezones.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -108,7 +108,7 @@ def test_drop_dst_boundary(self):
108108
False,
109109
False,
110110
],
111-
).as_unit("ns")
111+
)
112112
result = index.drop(index[0])
113113
tm.assert_index_equal(result, expected)
114114

‎pandas/tests/indexes/interval/test_formats.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -105,14 +105,14 @@ def test_timestamp_with_timezone(self):
105105
index = IntervalIndex(
106106
[
107107
Interval(
108-
Timestamp("2020-01-01", tz="UTC").as_unit("ns"),
109-
Timestamp("2020-01-02", tz="UTC").as_unit("ns"),
108+
Timestamp("2020-01-01", tz="UTC"),
109+
Timestamp("2020-01-02", tz="UTC"),
110110
)
111111
]
112112
)
113113
result = repr(index)
114114
expected = (
115115
"IntervalIndex([(2020-01-01 00:00:00+00:00, 2020-01-02 00:00:00+00:00]], "
116-
"dtype='interval[datetime64[ns, UTC], right]')"
116+
"dtype='interval[datetime64[s, UTC], right]')"
117117
)
118118
assert result == expected

‎pandas/tests/indexes/interval/test_interval_range.py

Lines changed: 6 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -170,14 +170,14 @@ def test_no_invalid_float_truncation(self, start, end, freq):
170170
"start, mid, end",
171171
[
172172
(
173-
Timestamp("2018-03-10", tz="US/Eastern").as_unit("ns"),
174-
Timestamp("2018-03-10 23:30:00", tz="US/Eastern").as_unit("ns"),
175-
Timestamp("2018-03-12", tz="US/Eastern").as_unit("ns"),
173+
Timestamp("2018-03-10", tz="US/Eastern"),
174+
Timestamp("2018-03-10 23:30:00", tz="US/Eastern"),
175+
Timestamp("2018-03-12", tz="US/Eastern"),
176176
),
177177
(
178-
Timestamp("2018-11-03", tz="US/Eastern").as_unit("ns"),
179-
Timestamp("2018-11-04 00:30:00", tz="US/Eastern").as_unit("ns"),
180-
Timestamp("2018-11-05", tz="US/Eastern").as_unit("ns"),
178+
Timestamp("2018-11-03", tz="US/Eastern"),
179+
Timestamp("2018-11-04 00:30:00", tz="US/Eastern"),
180+
Timestamp("2018-11-05", tz="US/Eastern"),
181181
),
182182
],
183183
)

‎pandas/tests/indexing/multiindex/test_setitem.py

Lines changed: 2 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -80,16 +80,10 @@ def test_setitem_multiindex2(self):
8080
def test_setitem_multiindex3(self):
8181
# GH#11372
8282
idx = MultiIndex.from_product(
83-
[
84-
["A", "B", "C"],
85-
date_range("2015-01-01", "2015-04-01", freq="MS", unit="s"),
86-
]
83+
[["A", "B", "C"], date_range("2015-01-01", "2015-04-01", freq="MS")]
8784
)
8885
cols = MultiIndex.from_product(
89-
[
90-
["foo", "bar"],
91-
date_range("2016-01-01", "2016-02-01", freq="MS", unit="s"),
92-
]
86+
[["foo", "bar"], date_range("2016-01-01", "2016-02-01", freq="MS")]
9387
)
9488

9589
df = DataFrame(

‎pandas/tests/reshape/concat/test_datetimes.py

Lines changed: 1 addition & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -268,8 +268,7 @@ def test_concat_NaT_series_dataframe_all_NaT(self, tz1, tz2):
268268
# GH 12396
269269

270270
# tz-naive
271-
# FIXME: without as_unit we get a FutureWarning about all-NA
272-
first = Series([pd.NaT, pd.NaT]).dt.tz_localize(tz1).dt.as_unit("s")
271+
first = Series([pd.NaT, pd.NaT]).dt.tz_localize(tz1)
273272
second = DataFrame(
274273
[
275274
[Timestamp("2015/01/01", tz=tz2)],

‎pandas/tests/tslibs/test_array_to_datetime.py

Lines changed: 0 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -184,7 +184,6 @@ def test_parsing_timezone_offsets(dt_string, expected_tz):
184184

185185

186186
def test_parsing_non_iso_timezone_offset():
187-
# FIXME: Timestamp(dt_string).unit should be nanos, is seconds
188187
dt_string = "01-01-2013T00:00:00.000000000+0000"
189188
arr = np.array([dt_string], dtype=object)
190189

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