[query] Refactor ggplot to use pandas, support alpha on histograms and bar charts

[johnc1231]

This PR:

1. Refactors listify to return pandas dataframes, and every geom to take in pandas dataframes. This significantly simplifies the code and should also speed things up.
2. Refactors the apply_to_fig method of most of the geoms to rely on a specification dict and then just loop over that. This simplifies adding a new argument / aesthethic. In the future, it may be best to just make all of the geoms take **kwargs so that arguments added to that dict will immediately be used for plotting, as right now I have to add something to geom_bar, GeomBar.__init__, and that dictionary for it to start showing up in plots.
3. Adds identity as a bar position, which means to plot bars on top of each other. This is useful along with the alpha argument added to bars and histograms, which sets transparency of points.

[johnc1231]

I'm still figuring out what the abstractions should be here. This refactoring has resulted in the apply_to_figure method of most geoms looking very similar, but still with little differences. Reluctant to commit to a very stringent class hierarchy yet and didn't want to further complicate this PR, but other than hline and vline, feels close to a world where each geom just overrides plot_one_group and the general looping over groups is handled by the parent class.

[patrick-schultz]

Looks good! Just an obsoleted comment.

[patrick-schultz]

You can leave this for future improvement, but I suspect you could do this more easily and faster with pandas groupby.

[johnc1231]

I am going to do this in future improvement, since I'm currently in the midst of refactoring this a bit due to a bug report about running out of colors to plot with.

Done