issues

Is your feature request related to a problem?

I was trying to store a zarr fstore and I got:

/opt/userenvs/ray.bell/autofront/lib/python3.9/site-packages/xarray/core/dataset.py:2060: SerializationWarning: saving variable None with floating point data as an integer dtype without any _FillValue to use for NaNs return to_zarr( # type: ignore

~~What I was seeing was a time coord which had encoding 'dtype': dtype('int64'). Storing the time this way lost the HH:MM on my datetime array.~~ I think I am seeing 'units': 'days since 2022-MM-DD 00:00:00' whereas it should be hours for my data.

Describe the solution you'd like

The message captures the variable/coord name instead of None

It could offer a solution such as "to store floating point data you could possibly use encoding={variable/coord: {"dtype": float, "_Fillvalue": np.nan}"

Describe alternatives you've considered

No response

Additional context

I'll try to come back and write a MCVE

WIP: you can get the warning message by doing: ds = xr.tutorial.open_dataset("air_temperature") ds["time"].encoding # {'units': 'hours since 1800-01-01', 'calendar': 'standard', 'dtype': dtype('float32')} ds.isel(time=0).to_zarr("tmp0.zarr", mode="w") /Users/ray/miniconda3/envs/main/lib/python3.9/site-packages/xarray/core/dataset.py:2060: SerializationWarning: saving variable None with floating point data as an integer dtype without any _FillValue to use for NaNs return to_zarr( # type: ignore

My guess if one of lat, lon, time, air is raising that message

Can't find the associated code in the repo that raises this. 2060 is to_zarr AFICT (https://github.com/pydata/xarray/blob/main/xarray/core/dataset.py#L2066)

Is your feature request related to a problem? Please describe. In the docs (http://xarray.pydata.org/en/stable/generated/xarray.Dataset.dropna.html) it says Dropping along multiple dimensions simultaneously is not yet supported. But I couldn't find a GitHub Issue open it. Apologies if there is one

Describe the solution you'd like da.dropna(['lat', 'lon], how="all") produces the same as da.dropna('lat', how="all").dropna('lon', how="all")

Is your feature request related to a problem?

I tend to use xr.cftime_range as a drop in for pandas.date_range. My only reason here is I may able to shave a line and not import pandas.

In doing xr.cftime_range("2020-01-01", periods=1, freq="W") I get

``` AttributeError Traceback (most recent call last) /opt/userenvs/ray.bell/main/lib/python3.9/site-packages/xarray/coding/cftime_offsets.py in to_offset(freq) 729 try: --> 730 freq_data = re.match(_PATTERN, freq).groupdict() 731 except AttributeError:

AttributeError: 'NoneType' object has no attribute 'groupdict'

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last) /tmp/ipykernel_549/3579801314.py in <module> ----> 1 xr.cftime_range("2020-01-01", periods=1, freq="W")

/opt/userenvs/ray.bell/main/lib/python3.9/site-packages/xarray/coding/cftime_offsets.py in cftime_range(start, end, periods, freq, normalize, name, closed, calendar) 1041 dates = _generate_linear_range(start, end, periods) 1042 else: -> 1043 offset = to_offset(freq) 1044 dates = np.array(list(_generate_range(start, end, periods, offset))) 1045

/opt/userenvs/ray.bell/main/lib/python3.9/site-packages/xarray/coding/cftime_offsets.py in to_offset(freq) 730 freq_data = re.match(_PATTERN, freq).groupdict() 731 except AttributeError: --> 732 raise ValueError("Invalid frequency string provided") 733 734 freq = freq_data["freq"]

ValueError: Invalid frequency string provided ```

In pandas I get

```

pd.date_range("2020-01-01", periods=1, freq="W") DatetimeIndex(['2020-01-05'], dtype='datetime64[ns]', freq='W-SUN') ```

Describe the solution you'd like

No response

Describe alternatives you've considered

Closing this issue as outside of scope

Additional context

No response

Is your feature request related to a problem?

For better or worse, I use xr.cftime_range interchangably with pd.date_range, mostly it is saves my importing pandas.

Pandas allows a string named "now" to be parsed in pd.date_range pd.date_range("2000-01-01", "now", freq="H") It would be nice if xr.cftime_range could do the same (see additional context for Traceback).

Describe the solution you'd like

Something like assert pd.date_range("2000-01-01", "now", freq="H") == xr.cftime_range("2000-01-01", "now", freq="H")

Describe alternatives you've considered

Close as not within the scope of xr.cftime_range

Additional context

xr.cftime_range("2000-01-01", "now", freq="H")

```python-traceback ValueError Traceback (most recent call last) /tmp/ipykernel_15451/3415490845.py in <module> ----> 1 xr.cftime_range("2000-01-01", "now", freq="H")

/opt/userenvs/ray.bell/main/lib/python3.9/site-packages/xarray/coding/cftime_offsets.py in cftime_range(start, end, periods, freq, normalize, name, closed, calendar) 982 start = _maybe_normalize_date(start, normalize) 983 if end is not None: --> 984 end = to_cftime_datetime(end, calendar) 985 end = _maybe_normalize_date(end, normalize) 986

/opt/userenvs/ray.bell/main/lib/python3.9/site-packages/xarray/coding/cftime_offsets.py in to_cftime_datetime(date_str_or_date, calendar) 697 "a calendar type must be provided" 698 ) --> 699 date, _ = _parse_iso8601_with_reso(get_date_type(calendar), date_str_or_date) 700 return date 701 elif isinstance(date_str_or_date, cftime.datetime):

/opt/userenvs/ray.bell/main/lib/python3.9/site-packages/xarray/coding/cftimeindex.py in _parse_iso8601_with_reso(date_type, timestr) 125 126 default = date_type(1, 1, 1) --> 127 result = parse_iso8601_like(timestr) 128 replace = {} 129

/opt/userenvs/ray.bell/main/lib/python3.9/site-packages/xarray/coding/cftimeindex.py in parse_iso8601_like(datetime_string) 115 if match: 116 return match.groupdict() --> 117 raise ValueError( 118 f"no ISO-8601 or cftime-string-like match for string: {datetime_string}" 119 )

ValueError: no ISO-8601 or cftime-string-like match for string: now ```

This is a paraphrase of a SO Q: https://stackoverflow.com/questions/66178846/read-in-authorized-opendap-url-using-xarray

Is your feature request related to a problem? Please describe. I would like to use xarray to read data stored at UCAR's Research Data Archive. To access data you have to create an account with a username and password.

Describe the solution you'd like url = ""https://rda.ucar.edu/thredds/dodsC/files/g/ds084.1/2020/20200101/gfs.0p25.2020010100.f000.grib2" ds = xr.open_dataset(url, backend_kwargs={"auth": ("username", "password")})

Describe alternatives you've considered You can read this file by create dot files in your home directory (https://stackoverflow.com/a/66179413/6046019)

Additional context The idea of "auth" comes from siphon (https://unidata.github.io/siphon/latest/examples/Basic_Usage.html#sphx-glr-examples-basic-usage-py).

The method xarray.Dataset.to_dask_dataframe exists and would like to make a feature request for the opposite xarray.Dataset.from_dask_dataframe. The conversation started over at dask but it was suggested by @shoyer to implement here first https://github.com/dask/dask/issues/6058

The docs current looks likes below. There are a lot of useful sections in Reading and Writing Files (http://xarray.pydata.org/en/latest/user-guide/io.html). Not sure if it's possible to add a drop down arrow (a third level) to see the sections from the table of contents on the left

https://github.com/pydata/xarray/discussions/5004

I just noticed that doing

da = xr.DataArray(np.random.rand(10, 10, 10), dims=('a', 'b', 'c')) da.to_pandas()

gives

```

KeyError Traceback (most recent call last) ~/local/bin/anaconda3/envs/test_env/lib/python3.8/site-packages/xarray/core/dataarray.py in to_pandas(self) 2397 try: -> 2398 constructor = constructors[self.ndim] 2399 except KeyError:

KeyError: 3

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last) <ipython-input-22-2c9fae875981> in <module> ----> 1 da.to_pandas()

~/local/bin/anaconda3/envs/test_env/lib/python3.8/site-packages/xarray/core/dataarray.py in to_pandas(self) 2398 constructor = constructors[self.ndim] 2399 except KeyError: -> 2400 raise ValueError( 2401 "cannot convert arrays with %s dimensions into " 2402 "pandas objects" % self.ndim

ValueError: cannot convert arrays with 3 dimensions into pandas objects ```

It is worth raising a suggestion (see below)? Or could you even do da.to_dataset(name='da').to_dataframe() under the hood. I feel the output would be what the user expects but I imagine that is not always true

da.to_dataset(name='da').to_dataframe()