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Address a few FutureWarnings (#380)

<!-- Please ensure the PR fulfills the following requirements! -->
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### Pull Request Checklist:
- [x] This PR addresses an already opened issue (for bug fixes /
features)
    - This PR fixes #xyz
- [x] (If applicable) Documentation has been added / updated (for bug
fixes / features).
- [x] (If applicable) Tests have been added.
- [x] This PR does not seem to break the templates.
- [x] CHANGES.rst has been updated (with summary of main changes).
- [x] Link to issue (:issue:`number`) and pull request (:pull:`number`)
has been added.

### What kind of change does this PR introduce?

* Addresses a few FutureWarning I encountered recently:
* `groupby` will change the default to `observed=True`. I think that our
implementation here does not care about `observed`, even if we use
categoricals, but I'm not 100% sure. We could use `observed=False` to
ensure no breaking change.
*
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.groupby.html
*
https://towardsdatascience.com/be-careful-when-using-pandas-groupby-with-categorical-data-type-a1d31f66b162
  * Changed a few of the old `pandas` codes that were missed.
  * Changed `pd.unique` to `np.unique`
* `pd.unique with argument that is not not a Series, Index,
ExtensionArray, or np.ndarray is deprecated and will raise in a future
version.`
* `intake_esm` no longer spams the warning about `applymap`, so our fix
was removed. It still has the "observed=True" spam, however.
    * Changed an implementation of inplace modifications to a DataFrame.
* `FutureWarning: A value is trying to be set on a copy of a DataFrame
or Series through chained assignment using an inplace method. The
behavior will change in pandas 3.0. This inplace method will never work
because the intermediate object on which we are setting values always
behaves as a copy.... (continued)

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