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/2568#issuecomment-1101516537,https://api.github.com/repos/pydata/xarray/issues/2568,1101516537,IC_kwDOAMm_X85Bp875,2448579,2022-04-18T15:51:57Z,2022-04-18T15:51:57Z,MEMBER,There's a longer discussion in #6377 so let's close this.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,383945783
https://github.com/pydata/xarray/issues/2568#issuecomment-441483832,https://api.github.com/repos/pydata/xarray/issues/2568,441483832,MDEyOklzc3VlQ29tbWVudDQ0MTQ4MzgzMg==,5635139,2018-11-25T23:30:36Z,2018-11-25T23:30:36Z,MEMBER,"Agree that `map` is not a good name (and I find the pandas API difficult in this area - each time I'm looking up what relabel / rename / map / select / filter does)

How about `match` / `switch` / `case`?

We would definitely use this. I agree it'd probably be used less in xarray than in pandas; though I'm keen to expand the API, in a deliberate and careful way, to some of the traditional pandas use-cases (but a small vote among many)
","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,383945783
https://github.com/pydata/xarray/issues/2568#issuecomment-441467391,https://api.github.com/repos/pydata/xarray/issues/2568,441467391,MDEyOklzc3VlQ29tbWVudDQ0MTQ2NzM5MQ==,1217238,2018-11-25T19:50:16Z,2018-11-25T19:50:16Z,MEMBER,"I would lean slightly against adding a dedicated method for this (but could be convinced if others are interested). Usually we copy pandas or numpy APIs, but `DataFrame.map` is a not a great name -- `map` means too many other things (e.g., consider the buildin `map`).

It might make sense to copy the design of `numpy.select` instead: https://docs.scipy.org/doc/numpy/reference/generated/numpy.select.html

e.g., you could write something like `xarray.select([ds < 0, ds < 10], [5, 10], default=15)`","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,383945783
https://github.com/pydata/xarray/issues/2568#issuecomment-441343812,https://api.github.com/repos/pydata/xarray/issues/2568,441343812,MDEyOklzc3VlQ29tbWVudDQ0MTM0MzgxMg==,1217238,2018-11-24T04:56:21Z,2018-11-24T04:56:33Z,MEMBER,"I would divide this into two steps: (1) write a function that does this on NumPy arrays and (2) apply it to xarray objects using `apply_ufunc`, e.g.,

```python
import numpy as np
import xarray as xr

def remap(array, mapping):
    return np.array([mapping[k] for k in array.ravel()]).reshape(array.shape)

ds = xr.Dataset({'test': ('t', [0, 1, 2])})
xr.apply_ufunc(remap, ds, kwargs=dict(mapping={0: 50, 1: 29, 2: 10}))
```
outputs:
```
<xarray.Dataset>
Dimensions:  (t: 3)
Dimensions without coordinates: t
Data variables:
    test     (t) int64 50 29 10
```","{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,383945783
https://github.com/pydata/xarray/issues/2568#issuecomment-441340466,https://api.github.com/repos/pydata/xarray/issues/2568,441340466,MDEyOklzc3VlQ29tbWVudDQ0MTM0MDQ2Ng==,1217238,2018-11-24T03:23:43Z,2018-11-24T03:23:43Z,MEMBER,"The usual way to do this in xarray would be to use `where()`, e.g., `xarray.where(ds == 0, 1, ds)` or `ds.where(ds == 0, 1)`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,383945783