This is a major release from 0.6. The main new feature is swarmplot which implements the beeswarm approach for drawing categorical scatterplots. There are also some performance improvements, bug fixes, and updates for compatibility with new versions of dependencies.
- Added the swarmplot function, which draws beeswarm plots. These are
categorical scatterplots, similar to those produced by stripplot,
but position of the points on the categorical axis is chosen to
avoid overlapping points. See the
categorical plot tutorial for more
information. - Added an additional rule when determining category order in
categorical plots. Now, when numeric variables are used in a
categorical role, the default behavior is to sort the unique levels
of the variable (i.e they will be in proper numerical order). This
can still be overridden by the appropriate{*_}order
parameter,
and variables with acategory
datatype will still follow the
category order even if the levels are strictly numerical. - Changed some of the stripplot defaults to be closer to swarmplot.
Points are somewhat smaller, have no outlines, and are not split by
default when usinghue
. - Changed how stripplot draws points when using
hue
nesting with
split=False
so that the differenthue
levels are not drawn
strictly on top of each other. - Improve performance for large dendrograms in clustermap.
- Added
font.size
to the plotting context definition so that the
default output fromplt.text
will be scaled appropriately. - Fixed a bug in clustermap when
fastcluster
is not installed. - Fixed a bug in the zscore calculation in clustermap.
- Fixed a bug in distplot where sometimes the default number of bins
would not be an integer. - Fixed a bug in stripplot where a legend item would not appear for a
hue
level if there were no observations in the first group of
points. - Heatmap colorbars are now rasterized for better performance in
vector plots. - Added workarounds for some matplotlib boxplot issues, such as
strange colors of outlier points. - Added workarounds for an issue where violinplot edges would be
missing or have random colors. - Added a workaround for an issue where only one heatmap cell would be
annotated on some matplotlib backends. - Fixed a bug on newer versions of matplotlib where a colormap would
be erroneously applied to scatterplots with only three observations. - Updated seaborn for compatibility with matplotlib 1.5.
- Added compatibility for various IPython (and Jupyter) versions in
functions that use widgets.