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}_ratioandcbar_posparameters. Additionally, the default organization and scaling with different figure sizes has been improved.Added the
corneroption toPairGridandpairplot()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
seedparameter, which can take either fixed seed (typically anint) or a numpy random number generator object (either the newernumpy.random.Generatoror the oldernumpy.random.mtrand.RandomState).Generalized the idea of “diagonal” axes in
PairGridto any axes that share an x and y variable.In
PairGrid, thehuevariable is now excluded from the default list of variables that make up the rows and columns of the grid.Exposed the
layout_padparameter inPairGridand 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
huevariable 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_kwsparameter toclustermap()to control the properties of the lines in the dendrogram.Added the ability to pass hierarchical label names to the
FacetGridlegend, 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
dropnainPairGridto 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
categorydata 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=Falseto progressively expand the x axis limits. Because there are currently limitations on how autoscaling works in matplotlib, the default value fortruncatein 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
sizescorrectly.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
Serieswith a non-default index.Fixed a bug when using
Seriesobjects as arguments forx_partialory_partialinregplot().Fixed a bug when passing a
normobject 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
numpychanges.Avoided error/warning in
lineplot()when plotting categoricals with empty levels.Allowed
colorsto 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
FacetGridlegend using matplotlib keyword arguments.