def test_flights_datetime_metrics_agg(self, agg):
ed_timestamps = self.ed_flights()["timestamp"]
expected_values = {
"min": pd.Timestamp("2018-01-01 00:00:00"),
"mean": pd.Timestamp("2018-01-21 19:20:45.564438232"),
"max": pd.Timestamp("2018-02-11 23:50:12"),
}
ed_metric = getattr(ed_timestamps, agg)()
assert_almost_equal(ed_metric, expected_values[agg])
def test_flights_datetime_metrics_agg_func(self, agg):
ed_timestamps = self.ed_flights()[["timestamp"]]
expected_values = {
"min": pd.Timestamp("2018-01-01 00:00:00"),
"mean": pd.Timestamp("2018-01-21 19:20:45.564438232"),
"max": pd.Timestamp("2018-02-11 23:50:12"),
}
ed_metric = getattr(ed_timestamps, agg)(numeric_only=False)
assert ed_metric.dtype == np.dtype("datetime64[ns]")
assert_almost_equal(ed_metric[0], expected_values[agg])
def test_flights_datetime_metrics_single_agg(self, agg):
ed_timestamps = self.ed_flights()[["timestamp"]]
expected_values = {
"min": pd.Timestamp("2018-01-01 00:00:00"),
"mean": pd.Timestamp("2018-01-21 19:20:45.564438232"),
"max": pd.Timestamp("2018-02-11 23:50:12"),
"nunique": 12236,
}
ed_metric = ed_timestamps.agg([agg])
if agg == "nunique":
# df with timestamp column should return int64
assert ed_metric.dtypes["timestamp"] == np.int64
else:
# df with timestamp column should return datetime64[ns]
assert ed_metric.dtypes["timestamp"] == np.dtype("datetime64[ns]")
assert_almost_equal(ed_metric["timestamp"][0], expected_values[agg])
def test_flights_datetime_metrics_agg(self):
ed_timestamps = self.ed_flights()[["timestamp"]]
expected_values = {
"max": pd.Timestamp("2018-02-11 23:50:12"),
"min": pd.Timestamp("2018-01-01 00:00:00"),
"mean": pd.Timestamp("2018-01-21 19:20:45.564438232"),
"sum": pd.NaT,
"mad": pd.NaT,
"var": pd.NaT,
"std": pd.NaT,
"nunique": 12236,
}
ed_metrics = ed_timestamps.agg(
self.funcs + self.extended_funcs + ["nunique"], numeric_only=False
)
ed_metrics_dict = ed_metrics["timestamp"].to_dict()
ed_metrics_dict.pop("median") # Median is tested below.
for key, expected_value in expected_values.items():
assert_almost_equal(ed_metrics_dict[key], expected_value)
def test_today() -> None:
c.assert_almost_equal(
datemore.datetime.Datetime.today().native(),
timezone.localize(datetime.datetime.today()),
)
def test_today() -> None:
c.assert_almost_equal(datemore.date.Date.today().native(),
datetime.date.today())