Unify categorical plots

[mwaskom]

This is a follow-on to #410. The majority of the changes are in terms of the implementation of things, but there are a few important new features and changes.

In short, the categorical distribution plots (boxplot, violinplot and stripplot) have been unified with the categorical estimation plots (barplot, pointplot, and countplot). From the user perspective, that means they all share a basic API. From the developer perspective, it means that as many common operations were abstracted out into the the underlying _CategoricalPlotter and _CategoricalStatPlotter classes. That means adding additional plot kinds in the future should be easier and more robust.

Demonstration of major new features

The main highlight in terms of new functionality is that barplot and pointplot can now draw horizontally:

sns.barplot(x="tip", y="day", data=tips)

Additionally, factorplot can use any of the categorical plot kinds:

sns.factorplot(x="age", y="embark_town", hue="sex", row="class",
               data=titanic[titanic.embark_town.notnull()],
               size=2, aspect=3.5, palette="Set3",
               kind="violin", split=True, cut=0, bw=.2)

API changes and new features

• The major API change in {bar,point,factor}_plot is that the x_order parameter has been renamed to order to reflect the fact that the categorical variable can be on the x or y axis.
• The ability to draw counts by passing only an x variable to barplot has been removed, but the new countplot function has been added to retain this functionality.
• In all places within the categorical plots, the representation and order of categorical levels is inferred from the data with an attempt to use pandas Categorical information if it exists. Otherwise, the default is now to use the order of levels as they appear in the dataframe rather than sorting by default. However, this behavior has not yet been changed in FacetGrid. That will likely be a different PR.
• Two parameters have been removed from the estimation plots (with attempts to catch and warn): hline and dropna
• This PR adds a compatibility layer for some of the API breaks in Overhaul of categorical distribution plots #410
• Added the scale parameter to pointplot, which scales the point size and linewidths by a single factor.
• Added the errcolor parameter to barplot and also now pass extra **kwargs down to plt.bar.
• Added the ax property to FacetGrid, which will give access to the main Axes in the case where there are no row or col facets.
• Added a more informative exception when string variables are named that don't appear in data.
• Fixed how the proxy artist used for generating the violinplot and boxplot legends is drawn to avoid errors when the first category has no data for a hue level.
• There are longer narrative explanations in the docstrings for all of the categorical plotting functions and copious examples for that will be executed and shown in the online API docs.

Linked issues:

This PR addresses several issues: #361, #416, #425, #435, #445, #448

Outstanding issues

• Update the release notes
• Update and reorganize the API docs homepage
• countplot needs some docstring examples
• Update the tutorials (may get punted on)

[mwaskom]

It would be great if people could pull this branch and throw all their weird, real-life data at it to check corner cases I may have missed with the test data/my own generally pretty clean experimental data.

[phobson]

Just want to say that this + the fact that factor plot takes row|col|hue arguments is

Huge

[phobson]

What's your the timeline for this? I can maybe take a crack at the tutorials (separate branch & PR) while testing. But that'll definitely have to wait for later in the week spilling over into next week.

[mwaskom]

The tutorial changes I have in mind are broader than just this PR -- now that I have an infrastructure for examples in the API docs, I want to move much of the nitty gritty stuff to there and make the tutorials more high-level and integrative. But I don't quite have a vision for what that will look like yet, so I'm not gonna hold up this PR for it.

[mwaskom]

Something I am considering is changing hue= in the categorical plots to by=, or possibly something different, to better differentiate it from what FacetGrid is doing with hue, which in almost all cases (except pointplot) is different.

[jankatins]

Just for reference: this only supports pandas >=0.15, in former versions Categorical.levels have to be used...