Closed
Description
When passing the values as a xarray.DataArray and specifying a unit, we get an error:
In [1]: import xarray as xr
In [2]: arr = xr.DataArray([1, 2, 3])
In [3]: pd.to_datetime(arr, unit='ns')
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-3-547fdd08888f> in <module>
----> 1 pd.to_datetime(arr, unit='ns')
~/miniconda3/envs/DS-geospatial/lib/python3.8/site-packages/pandas/core/tools/datetimes.py in to_datetime(arg, errors, dayfirst, yearfirst, utc, format, exact, unit, infer_datetime_format, origin, cache)
910 result = _convert_and_box_cache(arg, cache_array)
911 else:
--> 912 result = convert_listlike(arg, format)
913 else:
914 result = convert_listlike(np.array([arg]), format)[0]
~/miniconda3/envs/DS-geospatial/lib/python3.8/site-packages/pandas/core/tools/datetimes.py in _convert_listlike_datetimes(arg, format, name, tz, unit, errors, infer_datetime_format, dayfirst, yearfirst, exact)
354 if format is not None:
355 raise ValueError("cannot specify both format and unit")
--> 356 return _to_datetime_with_unit(arg, unit, name, tz, errors)
357 elif getattr(arg, "ndim", 1) > 1:
358 raise TypeError(
~/miniconda3/envs/DS-geospatial/lib/python3.8/site-packages/pandas/core/tools/datetimes.py in _to_datetime_with_unit(arg, unit, name, tz, errors)
526 tz_parsed = None
527 else:
--> 528 arr, tz_parsed = tslib.array_with_unit_to_datetime(arg, unit, errors=errors)
529
530 if errors == "ignore":
TypeError: Argument 'values' has incorrect type (expected numpy.ndarray, got DataArray)Since this is an array-like, I expect that we coerce that to a numpy array before passing to our cython routines (eg passing a list or Series does work this way).
And actually when not specifying the unit, it does work:
In [4]: pd.to_datetime(arr)
Out[4]:
DatetimeIndex(['1970-01-01 00:00:00.000000001',
'1970-01-01 00:00:00.000000002',
'1970-01-01 00:00:00.000000003'],
dtype='datetime64[ns]', freq=None)
Installed Versions
In [5]: pd.show_versions()
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.12.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-88-generic
Version : #99-Ubuntu SMP Thu Sep 23 17:29:00 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.28.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 2021.09.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : 2021.09.0
scipy : 1.7.1
sqlalchemy : None
tables : None
tabulate : None
xarray : 0.19.0
xlrd : None
xlwt : None
numba : 0.53.1