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  • jules-ch · 2 ✖

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  • Describe output time index after resampling in docs / docstring · 2 ✖

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  • NONE · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1480973335 https://github.com/pydata/xarray/issues/7662#issuecomment-1480973335 https://api.github.com/repos/pydata/xarray/issues/7662 IC_kwDOAMm_X85YRdwX jules-ch 43635101 2023-03-23T10:51:27Z 2023-03-23T10:51:27Z NONE

Values outside of the month are filled with NaN when aggregating after your month filter. It seems to be a side effect of grouping with a frequency.

 
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   Describe output time index after resampling in docs / docstring 1636435706
1480964097 https://github.com/pydata/xarray/issues/7662#issuecomment-1480964097 https://api.github.com/repos/pydata/xarray/issues/7662 IC_kwDOAMm_X85YRbgB jules-ch 43635101 2023-03-23T10:44:26Z 2023-03-23T10:46:22Z NONE

Idk if this comes from xarray, pandas seems to have the same behaviour:

```python import xarray as xr import pandas as pd import numpy as np

time = pd.date_range("2000-01-01", "2022-01-01", freq="1h") ds = xr.Dataset({"time": time, "v": ("time",np.random.rand(len(time)))}) ds

df = ds.to_dataframe() df = df[df.index.month.isin([6,7,8])] df.groupby(pd.Grouper(freq="D")).mean()

               v

time
2000-06-01 0.451577 2000-06-02 0.524039 2000-06-03 0.540553 2000-06-04 0.537686 2000-06-05 0.521928 ... ... 2021-08-27 0.441088 2021-08-28 0.473274 2021-08-29 0.455666 2021-08-30 0.559104 2021-08-31 0.424167

[7762 rows x 1 columns] ```

You can select your months after performing aggregation and you will have the correct number of rows

 
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   Describe output time index after resampling in docs / docstring 1636435706

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