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/5877#issuecomment-948691519,https://api.github.com/repos/pydata/xarray/issues/5877,948691519,IC_kwDOAMm_X844i-I_,10194086,2021-10-21T14:45:47Z,2021-10-21T14:45:47Z,MEMBER,"AFAIK bottleneck uses a less precise algorithm for sums than numpy (pydata/bottleneck#379). However, I don't know why this yields 0 at the beginning but not at the end.

A slightly more minimal example:

```python
import bottleneck as bn
import numpy as np
import pandas as pd

data = np.array(
    [
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.31,
        0.91999996,
        8.3,
        1.42,
        0.03,
        1.22,
        0.09999999,
        0.14,
        0.13,
        0.0,
        0.12,
        0.03,
        2.53,
        0.0,
        0.19999999,
        0.19999999,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
    ],
    dtype=""float32"",
)

bn.move_sum(data, window=3)
pd.Series(data).rolling(3).mean()
np.convolve(data, np.ones(3), 'valid') / 3
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1030768250
https://github.com/pydata/xarray/issues/5877#issuecomment-947893467,https://api.github.com/repos/pydata/xarray/issues/5877,947893467,IC_kwDOAMm_X844f7Tb,10194086,2021-10-20T17:41:04Z,2021-10-20T17:41:04Z,MEMBER,Thanks for the report. Without testing anything I suspect that this is due to the use of `float32` data and/ or bottleneck - see also  #1346. You can test this by uninstalling bottleneck (there is an option to disable bottleneck but it's not yet released (#5560).,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1030768250