(self)
| 1564 | tm.assert_series_equal(res_false, Series(exp_false)) |
| 1565 | |
| 1566 | def test_datetime_likes(self): |
| 1567 | dt = [ |
| 1568 | "2011-01-01", |
| 1569 | "2011-01-02", |
| 1570 | "2011-01-01", |
| 1571 | "NaT", |
| 1572 | "2011-01-03", |
| 1573 | "2011-01-02", |
| 1574 | "2011-01-04", |
| 1575 | "2011-01-01", |
| 1576 | "NaT", |
| 1577 | "2011-01-06", |
| 1578 | ] |
| 1579 | td = [ |
| 1580 | "1 days", |
| 1581 | "2 days", |
| 1582 | "1 days", |
| 1583 | "NaT", |
| 1584 | "3 days", |
| 1585 | "2 days", |
| 1586 | "4 days", |
| 1587 | "1 days", |
| 1588 | "NaT", |
| 1589 | "6 days", |
| 1590 | ] |
| 1591 | |
| 1592 | cases = [ |
| 1593 | np.array([Timestamp(d) for d in dt]), |
| 1594 | np.array([Timestamp(d, tz="US/Eastern") for d in dt]), |
| 1595 | np.array([Period(d, freq="D") for d in dt]), |
| 1596 | np.array([np.datetime64(d, "ns") for d in dt]), |
| 1597 | np.array([Timedelta(d) for d in td]), |
| 1598 | ] |
| 1599 | |
| 1600 | exp_first = np.array( |
| 1601 | [False, False, True, False, False, True, False, True, True, False] |
| 1602 | ) |
| 1603 | exp_last = np.array( |
| 1604 | [True, True, True, True, False, False, False, False, False, False] |
| 1605 | ) |
| 1606 | exp_false = exp_first | exp_last |
| 1607 | |
| 1608 | for case in cases: |
| 1609 | res_first = algos.duplicated(case, keep="first") |
| 1610 | tm.assert_numpy_array_equal(res_first, exp_first) |
| 1611 | |
| 1612 | res_last = algos.duplicated(case, keep="last") |
| 1613 | tm.assert_numpy_array_equal(res_last, exp_last) |
| 1614 | |
| 1615 | res_false = algos.duplicated(case, keep=False) |
| 1616 | tm.assert_numpy_array_equal(res_false, exp_false) |
| 1617 | |
| 1618 | # index |
| 1619 | for idx in [ |
| 1620 | Index(case), |
| 1621 | Index(case, dtype="category"), |
| 1622 | Index(case, dtype=object), |
| 1623 | ]: |
nothing calls this directly
no test coverage detected