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12 | 12 | date_range,
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13 | 13 | to_timedelta,
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14 | 14 | )
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15 |
| -from pandas.core.algorithms import checked_add_with_arr |
16 | 15 |
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17 | 16 | from .pandas_vb_common import numeric_dtypes
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18 | 17 |
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@@ -389,42 +388,6 @@ def time_add_timedeltas(self, df):
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389 | 388 | df["timedelta"] + df["timedelta"]
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390 | 389 |
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391 | 390 |
|
392 |
| -class AddOverflowScalar: |
393 |
| - params = [1, -1, 0] |
394 |
| - param_names = ["scalar"] |
395 |
| - |
396 |
| - def setup(self, scalar): |
397 |
| - N = 10**6 |
398 |
| - self.arr = np.arange(N) |
399 |
| - |
400 |
| - def time_add_overflow_scalar(self, scalar): |
401 |
| - checked_add_with_arr(self.arr, scalar) |
402 |
| - |
403 |
| - |
404 |
| -class AddOverflowArray: |
405 |
| - def setup(self): |
406 |
| - N = 10**6 |
407 |
| - self.arr = np.arange(N) |
408 |
| - self.arr_rev = np.arange(-N, 0) |
409 |
| - self.arr_mixed = np.array([1, -1]).repeat(N / 2) |
410 |
| - self.arr_nan_1 = np.random.choice([True, False], size=N) |
411 |
| - self.arr_nan_2 = np.random.choice([True, False], size=N) |
412 |
| - |
413 |
| - def time_add_overflow_arr_rev(self): |
414 |
| - checked_add_with_arr(self.arr, self.arr_rev) |
415 |
| - |
416 |
| - def time_add_overflow_arr_mask_nan(self): |
417 |
| - checked_add_with_arr(self.arr, self.arr_mixed, arr_mask=self.arr_nan_1) |
418 |
| - |
419 |
| - def time_add_overflow_b_mask_nan(self): |
420 |
| - checked_add_with_arr(self.arr, self.arr_mixed, b_mask=self.arr_nan_1) |
421 |
| - |
422 |
| - def time_add_overflow_both_arg_nan(self): |
423 |
| - checked_add_with_arr( |
424 |
| - self.arr, self.arr_mixed, arr_mask=self.arr_nan_1, b_mask=self.arr_nan_2 |
425 |
| - ) |
426 |
| - |
427 |
| - |
428 | 391 | hcal = pd.tseries.holiday.USFederalHolidayCalendar()
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429 | 392 | # These offsets currently raise a NotImplementedError with .apply_index()
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430 | 393 | non_apply = [
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|
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