DISCUSSION: policy for dependency updates that aren't covered by NEP 29

[NEP 29](https://numpy.org/neps/nep-0029-deprecation_policy.html), which [the pandas community has also been following](https://github.com/pandas-dev/pandas/issues/29034#issuecomment-546432309), has a timeline for Python and NumPy supported versions.

It does not have related recommendations for `pandas` and certainly not other packages we depend on such as `google-cloud-bigquery`, `google-cloud-bigquery-storage`, `pydata-google-auth`, `google-cloud-core`, `google-api-core`, `google-auth`, `google-auth-oauthlib`.

If I interpret the `NumPy` algorithm correctly, we need to support a two-year window.

> all minor versions of `package-name` released in the prior 24 months from the anticipated release date with a minimum of 3 minor versions of `package-name`

We're actually just about caught up with that in the `google-cloud-bigquery` dependency.

Our minimum version is `1.11.x`, which was released in April 2019. https://github.com/googleapis/python-bigquery/blob/master/CHANGELOG.md#1110 We'd be able to start incrementing minimum version to 1.12.0 in May.

Thoughts? Is 2 years the right window?