issue_comments: 601709733

This data as json

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/2922#issuecomment-601709733 https://api.github.com/repos/pydata/xarray/issues/2922 601709733 MDEyOklzc3VlQ29tbWVudDYwMTcwOTczMw== 7441788 2020-03-20T13:47:39Z 2020-03-20T16:31:14Z CONTRIBUTOR

@mathause, have you considered using these functions? - np.average() to calculate weighted mean(). - np.cov() to calculate weighted cov(), var(), and std(). - sp.stats.cumfreq() to calculate weighted median() (I haven't thought this through). - sp.spatial.distance.correlation() to calculate weighted corrcoef(). (Of course one could also calculate this from weighted cov() (see above), but first need to mask the two arrays simultaneously.) - sklearn.utils.extmath.weighted_mode() to calculate weighted mode(). - gmisclib.weighted_percentile.{wp,wtd_median}() to calculate weighted quantile() and median().

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   437765416