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  • dcherian · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
542257276 https://github.com/pydata/xarray/issues/2356#issuecomment-542257276 https://api.github.com/repos/pydata/xarray/issues/2356 MDEyOklzc3VlQ29tbWVudDU0MjI1NzI3Ng== dcherian 2448579 2019-10-15T15:01:33Z 2019-10-15T15:01:33Z MEMBER

Fixed in 0.13.0

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  New Resample-Syntax leading to cancellation of dimensions 349077990
412331569 https://github.com/pydata/xarray/issues/2356#issuecomment-412331569 https://api.github.com/repos/pydata/xarray/issues/2356 MDEyOklzc3VlQ29tbWVudDQxMjMzMTU2OQ== dcherian 2448579 2018-08-12T09:58:09Z 2018-08-12T09:58:09Z MEMBER

Oh sorry, i was mistaken. Looks like pandas does not require the repeated dimension. https://pandas.pydata.org/pandas-docs/stable/timeseries.html#resampling

The current API works like groupby but i don't think that was the original intent (#1269 #1272).

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  New Resample-Syntax leading to cancellation of dimensions 349077990
412109805 https://github.com/pydata/xarray/issues/2356#issuecomment-412109805 https://api.github.com/repos/pydata/xarray/issues/2356 MDEyOklzc3VlQ29tbWVudDQxMjEwOTgwNQ== dcherian 2448579 2018-08-10T15:02:00Z 2018-08-10T15:02:00Z MEMBER

The repeated dimension follows pandas syntax. It's nice because the syntax is similar to the usual reduction DataArray.sum().

.resample(TIMES='M').sum(dim='TIMES') should work as long as TIMES is datetime64.

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  New Resample-Syntax leading to cancellation of dimensions 349077990
411923961 https://github.com/pydata/xarray/issues/2356#issuecomment-411923961 https://api.github.com/repos/pydata/xarray/issues/2356 MDEyOklzc3VlQ29tbWVudDQxMTkyMzk2MQ== dcherian 2448579 2018-08-09T22:57:06Z 2018-08-09T22:57:06Z MEMBER

datamonth = data["TOT_PREC"].resample(time="M").sum(dim='time') should do what you want.

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  New Resample-Syntax leading to cancellation of dimensions 349077990

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