Big release with known bugs fixed and new features.

A copy of the changelog is pasted below.

API Changes

• ~plotnine.geoms.geom_smooth gained an extra parameter
  legend_fill_ratio that control the area of the legend that is
  filled to indicate confidence intervals. (32)
• plotnine.ggplot.save gained an extra parameter verbose. It no
  longer guesses when to print information and when not to.
• plotnine.ggplot.draw gained an extra parameter return_ggplot.
• If the minor_breaks parameter of scales is a callable, it now
  expects one argument, the limits. Previously it accepted breaks
  and limits.

New Features

• Added ~plotnine.animation.PlotnineAnimation for animations.
• Added ~plotnine.watermark.watermark for watermarks.
• Added datetime scales for alpha, colour, fill and size
  aesthetics

Enhancements

• Changed parameter settings for ~plotnine.stats.stat_smooth.

  1. Default span=0.75 instead of 2/3
  2. When using loess smoothing, the control parameter surface is
     only set to the value 'direct' if predictions will be made
     outside the data range.

• Better control of scale limits. You can now specify individual
  limits of a scale.

  scale_y_continuous(limits=(0, None))
  xlim(None, 100)
  

  You can also use ~plotnine.scales.expand_limits

• Low and high ~plotnine.scales.scale limits can now be expanded
  separately with different factors multiplicative and additive
  factors.

• The layer parameter show_legend can now accept a dict for finer
  grained control of which aesthetics to exclude in the legend.

• Infinite values are removed before statistical computations stats
  (40).

  stats also gained new parameter na_rm, that controls whether
  missing values are removed before statistical computations.

• ~plotnine.qplot can now use the name and a Pandas series to label
  the scales of the aesthetics.

• You can now put stuff to add to a ggplot object into a list and add
  that that instead. No need to wrap the list around the internal
  class Layers.

  lst = [geom_point(), geom_line()]
  g = ggplot(df, aes('x', 'y'))
  print(g + lst)
  

  Using a list allows you to bundle up objects. It can be convenient
  when creating some complicated plots. See the Periodic Table
  Example.

Bug Fixes

• Fixed bug where facetting led to a reordering of the data. This
  would manifest as a bug for geoms where order was important. (26)
• Fix bug where facetting by a column whose name (eg. class) is a
  python keyword resulted in an exception. (28)
• Fix bug where y-axis scaling was calculated from the xlim
  argument.
• Fix bug where initialising geoms from stats, and positions from
  geoms, when passed as classes (e.g. stat_smooth(geom=geom_point),
  would fail.
• Fixed bug in plotnine.ggplot.save where s