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/issues/3267#issuecomment-1528597777,https://api.github.com/repos/pydata/xarray/issues/3267,1528597777,IC_kwDOAMm_X85bHI0R,2448579,2023-04-29T03:30:20Z,2023-04-29T03:30:20Z,MEMBER,Should be better now with `flox` installed,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,485508509
https://github.com/pydata/xarray/issues/3267#issuecomment-526021848,https://api.github.com/repos/pydata/xarray/issues/3267,526021848,MDEyOklzc3VlQ29tbWVudDUyNjAyMTg0OA==,2443309,2019-08-29T04:54:27Z,2019-08-29T04:54:27Z,MEMBER,We should probably add some airspeed benchmarks for resample ops. I'm just noticing we don't have any yet: https://pandas.pydata.org/speed/xarray/,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,485508509
https://github.com/pydata/xarray/issues/3267#issuecomment-526010224,https://api.github.com/repos/pydata/xarray/issues/3267,526010224,MDEyOklzc3VlQ29tbWVudDUyNjAxMDIyNA==,5635139,2019-08-29T03:53:55Z,2019-08-29T03:53:55Z,MEMBER,"I do get a difference between master and xarray 0.11.3, although closer to 15%:

```python

In [1]: import numpy as np
   ...: import xarray as xr
   ...: import pandas as pd
   ...: import time
   ...:
   ...: size = 1000000
   ...: data = np.random.random(size)
   ...: times = pd.date_range('2019-01-01', periods=size, freq='ms')
   ...: da = xr.DataArray(data, dims=['time'], coords={'time': times})
   ...:
   ...: start = time.time()
   ...:
   ...: da.resample(time='s').mean()
   ...:
   ...: print('Elapsed time: ' + str(time.time() - start))
   ...: print('xarray version: ' + str(xr.__version__))
/usr/local/lib/python3.7/site-packages/xarray/core/merge.py:10: FutureWarning: The Panel class is removed from pandas. Accessing it from the top-level namespace will also be removed in the next version
  PANDAS_TYPES = (pd.Series, pd.DataFrame, pd.Panel)
Elapsed time: 0.1272139549255371
xarray version: 0.11.3
```

```python

In [1]: import numpy as np
   ...: import xarray as xr
   ...: import pandas as pd
   ...: import time
   ...:
   ...: size = 1000000
   ...: data = np.random.random(size)
   ...: times = pd.date_range('2019-01-01', periods=size, freq='ms')
   ...: da = xr.DataArray(data, dims=['time'], coords={'time': times})
   ...:
   ...: start = time.time()
   ...:
   ...: da.resample(time='s').mean()
   ...:
   ...: print('Elapsed time: ' + str(time.time() - start))
   ...: print('xarray version: ' + str(xr.__version__))
Elapsed time: 0.14267230033874512
xarray version: 0.12.3+74.ge3b3bed2
```

...so I'm guessing it's another dependency. It looks like you have bottleneck installed. 

Anyone have other ideas for what might be causing this @pydata/xarray ?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,485508509
https://github.com/pydata/xarray/issues/3267#issuecomment-526008533,https://api.github.com/repos/pydata/xarray/issues/3267,526008533,MDEyOklzc3VlQ29tbWVudDUyNjAwODUzMw==,20617032,2019-08-29T03:44:42Z,2019-08-29T03:44:42Z,NONE,"I seem to still have a discrepancy

Elapsed time: 1.3887653350830078
xarray version: 0.12.3+79.gaaeea625

Elapsed time: 0.12198281288146973
xarray version: 0.11.3

(This is on a different computer) ","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,485508509
https://github.com/pydata/xarray/issues/3267#issuecomment-525086439,https://api.github.com/repos/pydata/xarray/issues/3267,525086439,MDEyOklzc3VlQ29tbWVudDUyNTA4NjQzOQ==,5635139,2019-08-27T00:36:29Z,2019-08-27T00:36:29Z,MEMBER,"Thanks for the clear issue @aspitarl 

I tried on master - it looks like it's back to the old timings. Do you want to confirm?

```python

In [1]:
   ...:
   ...: import numpy as np
   ...: import xarray as xr
   ...: import pandas as pd
   ...: import time
   ...:
   ...: size = 1000000
   ...: data = np.random.random(size)
   ...: times = pd.date_range('2019-01-01', periods=size, freq='ms')
   ...: da = xr.DataArray(data, dims=['time'], coords={'time': times})
   ...:
   ...: start = time.time()
   ...:
   ...: da.resample(time='s').mean()
   ...:
   ...: print('Elapsed time: ' + str(time.time() - start))
   ...: print('xarray version: ' + str(xr.__version__))
Elapsed time: 0.19948101043701172
xarray version: 0.12.3+74.ge3b3bed2
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,485508509