def METHOD_NAME():
    # Make a timeseries that has 14 days of NaN, than 14 days of increasing values. The first
    # 100_000 is there so the NaN form a gap that isn't dropped by unrelated code.
    values = [100_000] + [float("NaN")] * 14 + list(range(100_000, 114_000, 1_000))
    assert len(values) == 29
    ds_in = test_helpers.build_default_region_dataset({CommonFields.NEW_CASES: values})
    tail_filter, ds_out = TailFilter.run(ds_in, [CommonFields.NEW_CASES])
    _assert_tail_filter_counts(tail_filter, skipped_na_mean=1)
    test_helpers.assert_dataset_like(ds_out, ds_in, drop_na_dates=True)