|
15 | 15 | tslib,
|
16 | 16 | )
|
17 | 17 | from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
|
18 |
| -from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime |
19 | 18 |
|
20 | 19 | from pandas import Timestamp
|
21 | 20 | import pandas._testing as tm
|
@@ -307,63 +306,3 @@ def test_datetime_subclass(data, expected):
|
307 | 306 |
|
308 | 307 | expected = np.array(expected, dtype="M8[us]")
|
309 | 308 | tm.assert_numpy_array_equal(result, expected)
|
310 |
| - |
311 |
| - |
312 |
| -class TestArrayToDatetimeResolutionInference: |
313 |
| - # TODO: tests that include tzs, ints |
314 |
| - |
315 |
| - def test_infer_homogeoneous_datetimes(self): |
316 |
| - dt = datetime(2023, 10, 27, 18, 3, 5, 678000) |
317 |
| - arr = np.array([dt, dt, dt], dtype=object) |
318 |
| - result, tz = tslib.array_to_datetime(arr, creso=creso_infer) |
319 |
| - assert tz is None |
320 |
| - expected = np.array([dt, dt, dt], dtype="M8[us]") |
321 |
| - tm.assert_numpy_array_equal(result, expected) |
322 |
| - |
323 |
| - def test_infer_homogeoneous_date_objects(self): |
324 |
| - dt = datetime(2023, 10, 27, 18, 3, 5, 678000) |
325 |
| - dt2 = dt.date() |
326 |
| - arr = np.array([None, dt2, dt2, dt2], dtype=object) |
327 |
| - result, tz = tslib.array_to_datetime(arr, creso=creso_infer) |
328 |
| - assert tz is None |
329 |
| - expected = np.array([np.datetime64("NaT"), dt2, dt2, dt2], dtype="M8[s]") |
330 |
| - tm.assert_numpy_array_equal(result, expected) |
331 |
| - |
332 |
| - def test_infer_homogeoneous_dt64(self): |
333 |
| - dt = datetime(2023, 10, 27, 18, 3, 5, 678000) |
334 |
| - dt64 = np.datetime64(dt, "ms") |
335 |
| - arr = np.array([None, dt64, dt64, dt64], dtype=object) |
336 |
| - result, tz = tslib.array_to_datetime(arr, creso=creso_infer) |
337 |
| - assert tz is None |
338 |
| - expected = np.array([np.datetime64("NaT"), dt64, dt64, dt64], dtype="M8[ms]") |
339 |
| - tm.assert_numpy_array_equal(result, expected) |
340 |
| - |
341 |
| - def test_infer_homogeoneous_timestamps(self): |
342 |
| - dt = datetime(2023, 10, 27, 18, 3, 5, 678000) |
343 |
| - ts = Timestamp(dt).as_unit("ns") |
344 |
| - arr = np.array([None, ts, ts, ts], dtype=object) |
345 |
| - result, tz = tslib.array_to_datetime(arr, creso=creso_infer) |
346 |
| - assert tz is None |
347 |
| - expected = np.array([np.datetime64("NaT")] + [ts.asm8] * 3, dtype="M8[ns]") |
348 |
| - tm.assert_numpy_array_equal(result, expected) |
349 |
| - |
350 |
| - def test_infer_homogeoneous_datetimes_strings(self): |
351 |
| - item = "2023-10-27 18:03:05.678000" |
352 |
| - arr = np.array([None, item, item, item], dtype=object) |
353 |
| - result, tz = tslib.array_to_datetime(arr, creso=creso_infer) |
354 |
| - assert tz is None |
355 |
| - expected = np.array([np.datetime64("NaT"), item, item, item], dtype="M8[us]") |
356 |
| - tm.assert_numpy_array_equal(result, expected) |
357 |
| - |
358 |
| - def test_infer_heterogeneous(self): |
359 |
| - dtstr = "2023-10-27 18:03:05.678000" |
360 |
| - |
361 |
| - arr = np.array([dtstr, dtstr[:-3], dtstr[:-7], None], dtype=object) |
362 |
| - result, tz = tslib.array_to_datetime(arr, creso=creso_infer) |
363 |
| - assert tz is None |
364 |
| - expected = np.array(arr, dtype="M8[us]") |
365 |
| - tm.assert_numpy_array_equal(result, expected) |
366 |
| - |
367 |
| - result, tz = tslib.array_to_datetime(arr[::-1], creso=creso_infer) |
368 |
| - assert tz is None |
369 |
| - tm.assert_numpy_array_equal(result, expected[::-1]) |
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