CI: Run all code checks even if one fails
xref https://github.com/pandas-dev/pandas/pull/47469#issuecomment-1163790491=

Solution gleaned from: https://stackoverflow.com/a/58859404

Want to `always()` run all these steps _If_ pandas was built correctly

Note: Cannot use `continue-on-error` because if a check fails the build will still pass which we don't want https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepscontinue-on-error=
If we have this does it make sense to split the steps into multiple jobs? And have one upstream job that builds pandas so that work isn't duplicated. We could use that upstream job for ASV and docs as well. +1 to have one build pandas job for all the checks that share the `environment.yml` dependencies. I am slightly partial to the current job grouping though. Is there a max number of jobs that can run in parallel across workflows? I couldn't immediately find it in the docs  I monitored the load on the Pandas CI pipeline for the past 14 days (with the help of another GHA pipeline :)) and this is the quantiles

```
0.0: 0
5.0: 0
10.0: 0
15.0: 0
20.0: 0
25.0: 0
30.0: 0
35.0: 2
40.0: 2
45.0: 2
50.0: 3
55.0: 5
60.0: 5
65.0: 5
70.0: 7
75.0: 8
80.0: 10
85.0: 14
90.0: 20
```

Checked every 13 minutes. 65% of the time we have < 5 workflows running, for a maximum of 5 * 17 = 85 parallel jobs (we have 17 jobs in the Ubuntu workflow). So I'm not sure it's worth reducing the number of parallel jobs right now. We might want to optimize latency-to-first-valuable-feedback instead.