Both pandas-gbq and google-cloud-bigquery are doing many of the same things, and increasingly so (e.g. .to_dataframe() in google-cloud-bigquery)

• Are there different use cases? Can we define those?
• Should we focus development on one and wrap the other? Even if not wholly, for a subset of functionality?
• Is there some direction from Google? @tswast spends a lot of time on both libraries so he is probably best placed to offer guidance