v0.9.1 (January 2020)#
This is a minor release with a number of bug fixes and adaptations to changes in seaborn’s dependencies. There are also several new features.
This is the final version of seaborn that will support Python 2.7 or 3.5.
New features#
Added more control over the arrangement of the elements drawn by
clustermap()
with the{dendrogram,colors}_ratio
andcbar_pos
parameters. Additionally, the default organization and scaling with different figure sizes has been improved.Added the
corner
option toPairGrid
andpairplot()
to make a grid without the upper triangle of bivariate axes.Added the ability to seed the random number generator for the bootstrap used to define error bars in several plots. Relevant functions now have a
seed
parameter, which can take either fixed seed (typically anint
) or a numpy random number generator object (either the newernumpy.random.Generator
or the oldernumpy.random.mtrand.RandomState
).Generalized the idea of “diagonal” axes in
PairGrid
to any axes that share an x and y variable.In
PairGrid
, thehue
variable is now excluded from the default list of variables that make up the rows and columns of the grid.Exposed the
layout_pad
parameter inPairGrid
and set a smaller default than what matptlotlib sets for more efficient use of space in dense grids.It is now possible to force a categorical interpretation of the
hue
variable in a relational plot by passing the name of a categorical palette (e.g."deep"
, or"Set2"
). This complements the (previously supported) option of passing a list/dict of colors.Added the
tree_kws
parameter toclustermap()
to control the properties of the lines in the dendrogram.Added the ability to pass hierarchical label names to the
FacetGrid
legend, which also fixes a bug inrelplot()
when the same label appeared in different semantics.Improved support for grouping observations based on pandas index information in categorical plots.
Bug fixes and adaptations#
Avoided an error when singular data is passed to
kdeplot()
, issuing a warning instead. This makespairplot()
more robust.Fixed the behavior of
dropna
inPairGrid
to properly exclude null datapoints from each plot when set toTrue
.Fixed an issue where
regplot()
could interfere with other axes in a multi-plot matplotlib figure.Semantic variables with a
category
data type will always be treated as categorical in relational plots.Avoided a warning about color specifications that arose from
boxenplot()
on newer matplotlibs.Adapted to a change in how matplotlib scales axis margins, which caused multiple calls to
regplot()
withtruncate=False
to progressively expand the x axis limits. Because there are currently limitations on how autoscaling works in matplotlib, the default value fortruncate
in seaborn has also been changed toTrue
.Relational plots no longer error when hue/size data are inferred to be numeric but stored with a string datatype.
Relational plots now consider semantics with only a single value that can be interpreted as boolean (0 or 1) to be categorical, not numeric.
Relational plots now handle list or dict specifications for
sizes
correctly.Fixed an issue in
pointplot()
where missing levels of a hue variable would cause an exception after a recent update in matplotlib.Fixed a bug when setting the rotation of x tick labels on a
FacetGrid
.Fixed a bug where values would be excluded from categorical plots when only one variable was a pandas
Series
with a non-default index.Fixed a bug when using
Series
objects as arguments forx_partial
ory_partial
inregplot()
.Fixed a bug when passing a
norm
object and using color annotations inclustermap()
.Fixed a bug where annotations were not rearranged to match the clustering in
clustermap()
.Fixed a bug when trying to call
set()
while specifying a list of colors for the palette.Fixed a bug when resetting the color code short-hands to the matplotlib default.
Avoided errors from stricter type checking in upcoming
numpy
changes.Avoided error/warning in
lineplot()
when plotting categoricals with empty levels.Allowed
colors
to be passed through to a bivariatekdeplot()
.Standardized the output format of custom color palette functions.
Fixed a bug where legends for numerical variables in a relational plot could show a surprisingly large number of decimal places.
Improved robustness to missing values in distribution plots.
Made it possible to specify the location of the
FacetGrid
legend using matplotlib keyword arguments.