Closed
Description
Pandas version checks
-
I have checked that this issue has not already been reported.
-
I have confirmed this bug exists on the latest version of pandas.
-
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
dates = pd.date_range("2022", periods=3, tz="UTC")
print(pd.IntervalIndex.from_arrays(dates[:-1], dates[1:]))
print(
pd.IntervalIndex.from_arrays(
["2022-01-01", "2022-01-02"],
["2022-01-02", "2022-01-03"],
dtype="interval[datetime64[ns, UTC], right]",
)
)
Issue Description
raises TypeError: data type 'interval[datetime64[ns, UTC], right]' not understood
xref #46666
works for Interval of naive timeseries...
dates = pd.date_range("2022", periods=3)
print(pd.IntervalIndex.from_arrays(dates[:-1], dates[1:]))
print(
pd.IntervalIndex.from_arrays(
["2022-01-01", "2022-01-02"],
["2022-01-02", "2022-01-03"],
dtype="interval[datetime64[ns], right]",
)
)
Expected Behavior
IntervalIndex([(2022-01-01, 2022-01-02], (2022-01-02, 2022-01-03]], dtype='interval[datetime64[ns, UTC], right]')
Installed Versions
.