|
1 |
| -from datetime import datetime |
2 | 1 | from io import StringIO
|
3 | 2 |
|
4 | 3 | import numpy as np
|
5 |
| -import pytest |
6 | 4 |
|
7 | 5 | from pandas._libs.tslib import iNaT
|
8 | 6 |
|
9 | 7 | import pandas as pd
|
10 |
| -from pandas import ( |
11 |
| - DataFrame, |
12 |
| - DatetimeIndex, |
13 |
| - NaT, |
14 |
| - Series, |
15 |
| - Timestamp, |
16 |
| - date_range, |
17 |
| - timedelta_range, |
18 |
| -) |
| 8 | +from pandas import DataFrame, DatetimeIndex, Series, date_range, timedelta_range |
19 | 9 | import pandas._testing as tm
|
20 | 10 |
|
21 | 11 |
|
@@ -225,82 +215,6 @@ def test_asfreq_resample_set_correct_freq(self):
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225 | 215 | # does .resample() set .freq correctly?
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226 | 216 | assert df.resample("D").asfreq().index.freq == "D"
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227 | 217 |
|
228 |
| - def test_pickle(self): |
229 |
| - |
230 |
| - # GH4606 |
231 |
| - p = tm.round_trip_pickle(NaT) |
232 |
| - assert p is NaT |
233 |
| - |
234 |
| - idx = pd.to_datetime(["2013-01-01", NaT, "2014-01-06"]) |
235 |
| - idx_p = tm.round_trip_pickle(idx) |
236 |
| - assert idx_p[0] == idx[0] |
237 |
| - assert idx_p[1] is NaT |
238 |
| - assert idx_p[2] == idx[2] |
239 |
| - |
240 |
| - # GH11002 |
241 |
| - # don't infer freq |
242 |
| - idx = date_range("1750-1-1", "2050-1-1", freq="7D") |
243 |
| - idx_p = tm.round_trip_pickle(idx) |
244 |
| - tm.assert_index_equal(idx, idx_p) |
245 |
| - |
246 |
| - @pytest.mark.parametrize("tz", [None, "Asia/Tokyo", "US/Eastern"]) |
247 |
| - def test_setops_preserve_freq(self, tz): |
248 |
| - rng = date_range("1/1/2000", "1/1/2002", name="idx", tz=tz) |
249 |
| - |
250 |
| - result = rng[:50].union(rng[50:100]) |
251 |
| - assert result.name == rng.name |
252 |
| - assert result.freq == rng.freq |
253 |
| - assert result.tz == rng.tz |
254 |
| - |
255 |
| - result = rng[:50].union(rng[30:100]) |
256 |
| - assert result.name == rng.name |
257 |
| - assert result.freq == rng.freq |
258 |
| - assert result.tz == rng.tz |
259 |
| - |
260 |
| - result = rng[:50].union(rng[60:100]) |
261 |
| - assert result.name == rng.name |
262 |
| - assert result.freq is None |
263 |
| - assert result.tz == rng.tz |
264 |
| - |
265 |
| - result = rng[:50].intersection(rng[25:75]) |
266 |
| - assert result.name == rng.name |
267 |
| - assert result.freqstr == "D" |
268 |
| - assert result.tz == rng.tz |
269 |
| - |
270 |
| - nofreq = DatetimeIndex(list(rng[25:75]), name="other") |
271 |
| - result = rng[:50].union(nofreq) |
272 |
| - assert result.name is None |
273 |
| - assert result.freq == rng.freq |
274 |
| - assert result.tz == rng.tz |
275 |
| - |
276 |
| - result = rng[:50].intersection(nofreq) |
277 |
| - assert result.name is None |
278 |
| - assert result.freq == rng.freq |
279 |
| - assert result.tz == rng.tz |
280 |
| - |
281 |
| - def test_from_M8_structured(self): |
282 |
| - dates = [(datetime(2012, 9, 9, 0, 0), datetime(2012, 9, 8, 15, 10))] |
283 |
| - arr = np.array(dates, dtype=[("Date", "M8[us]"), ("Forecasting", "M8[us]")]) |
284 |
| - df = DataFrame(arr) |
285 |
| - |
286 |
| - assert df["Date"][0] == dates[0][0] |
287 |
| - assert df["Forecasting"][0] == dates[0][1] |
288 |
| - |
289 |
| - s = Series(arr["Date"]) |
290 |
| - assert isinstance(s[0], Timestamp) |
291 |
| - assert s[0] == dates[0][0] |
292 |
| - |
293 |
| - def test_get_level_values_box(self): |
294 |
| - from pandas import MultiIndex |
295 |
| - |
296 |
| - dates = date_range("1/1/2000", periods=4) |
297 |
| - levels = [dates, [0, 1]] |
298 |
| - codes = [[0, 0, 1, 1, 2, 2, 3, 3], [0, 1, 0, 1, 0, 1, 0, 1]] |
299 |
| - |
300 |
| - index = MultiIndex(levels=levels, codes=codes) |
301 |
| - |
302 |
| - assert isinstance(index.get_level_values(0)[0], Timestamp) |
303 |
| - |
304 | 218 | def test_view_tz(self):
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305 | 219 | # GH#24024
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306 | 220 | ser = pd.Series(pd.date_range("2000", periods=4, tz="US/Central"))
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