html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/4454#issuecomment-701106214,https://api.github.com/repos/pydata/xarray/issues/4454,701106214,MDEyOklzc3VlQ29tbWVudDcwMTEwNjIxNA==,5635139,2020-09-30T01:31:34Z,2020-09-30T01:31:34Z,MEMBER,Thanks a lot @andrewpauling ! ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-701095631,https://api.github.com/repos/pydata/xarray/issues/4454,701095631,MDEyOklzc3VlQ29tbWVudDcwMTA5NTYzMQ==,6628425,2020-09-30T00:50:55Z,2020-09-30T00:50:55Z,MEMBER,Thanks again @andrewpauling!,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-700915602,https://api.github.com/repos/pydata/xarray/issues/4454,700915602,MDEyOklzc3VlQ29tbWVudDcwMDkxNTYwMg==,22488770,2020-09-29T18:56:17Z,2020-09-29T18:56:17Z,CONTRIBUTOR,Cool! Thank you all for your help.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-700914758,https://api.github.com/repos/pydata/xarray/issues/4454,700914758,MDEyOklzc3VlQ29tbWVudDcwMDkxNDc1OA==,5635139,2020-09-29T18:54:54Z,2020-09-29T18:54:54Z,MEMBER,"Great, let's merge on green!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-698670864,https://api.github.com/repos/pydata/xarray/issues/4454,698670864,MDEyOklzc3VlQ29tbWVudDY5ODY3MDg2NA==,6628425,2020-09-25T01:30:05Z,2020-09-25T23:56:23Z,MEMBER,"You're absolutely right @andrewpauling -- pandas currently doesn't seem to have overflow protection in the case of casting `timedelta64` types.  I wrongly assumed that it would!  I went ahead and opened an issue there: https://github.com/pandas-dev/pandas/issues/36615.  We'll see what they say.

For now maybe you can add the test and attach an [expected failure decorator](https://docs.pytest.org/en/latest/skipping.html#xfail-mark-test-functions-as-expected-to-fail) to it?

In researching this, I came across https://github.com/numpy/numpy/issues/16352; if that eventually gets addressed this might all be moot.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-699204478,https://api.github.com/repos/pydata/xarray/issues/4454,699204478,MDEyOklzc3VlQ29tbWVudDY5OTIwNDQ3OA==,5635139,2020-09-25T23:05:07Z,2020-09-25T23:05:07Z,MEMBER,"Excellent, thanks @andrewpauling ! LGTM","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-699190673,https://api.github.com/repos/pydata/xarray/issues/4454,699190673,MDEyOklzc3VlQ29tbWVudDY5OTE5MDY3Mw==,22488770,2020-09-25T22:33:45Z,2020-09-25T22:33:45Z,CONTRIBUTOR,"Thanks @spencerkclark, I have added a test with the decorator you mentioned and edited the formatting in the whats-new file as above. Hopefully it should be good now.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-698507141,https://api.github.com/repos/pydata/xarray/issues/4454,698507141,MDEyOklzc3VlQ29tbWVudDY5ODUwNzE0MQ==,22488770,2020-09-24T18:17:52Z,2020-09-24T18:17:52Z,CONTRIBUTOR,"> Nice! Could you also add a similar test for `timedelta64` data?

Hi @spencerkclark, I have been trying to work on a test for timedelta64 data but I don't think I understand timedelta data very well. I can't seem to come up with an example that raises an `OutOfBoundsTimedelta` error. From what I found online (https://pandas.pydata.org/pandas-docs/stable/user_guide/timedeltas.html), the valid range for nanosecond precision should be about 100000 days. When I try to input an np.timedelta64[D] object of more days than that, it just overflows and gives nonsense without throwing an error. Do you have any suggestions?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-698069611,https://api.github.com/repos/pydata/xarray/issues/4454,698069611,MDEyOklzc3VlQ29tbWVudDY5ODA2OTYxMQ==,5635139,2020-09-24T02:13:29Z,2020-09-24T02:13:29Z,MEMBER,"It looks great! I made one suggestion. 

Any thoughts from others?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-698049781,https://api.github.com/repos/pydata/xarray/issues/4454,698049781,MDEyOklzc3VlQ29tbWVudDY5ODA0OTc4MQ==,22488770,2020-09-24T01:00:44Z,2020-09-24T01:00:44Z,CONTRIBUTOR,"Hi @max-sixty, I have just added what I hope is a good test, I haven't written one before, but tried to base it on others in the test_variable file","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196
https://github.com/pydata/xarray/pull/4454#issuecomment-698032306,https://api.github.com/repos/pydata/xarray/issues/4454,698032306,MDEyOklzc3VlQ29tbWVudDY5ODAzMjMwNg==,5635139,2020-09-23T23:56:20Z,2020-09-23T23:56:20Z,MEMBER,"Thanks @andrewpauling , this looks good.

Could you add a test?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,707745196