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.
Added more control over the arrangement of the elements drawn by
cbar_posparameters. Additionally, the default organization and scaling with different figure sizes has been improved.
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 an
int) or a numpy random number generator object (either the newer
numpy.random.Generatoror the older
Generalized the idea of “diagonal” axes in
PairGridto any axes that share an x and y variable.
huevariable is now excluded from the default list of variables that make up the rows and columns of the grid.
PairGridand 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.
"Set2"). This complements the (previously supported) option of passing a list/dict of colors.
clustermap()to control the properties of the lines in the dendrogram.
Improved support for grouping observations based on pandas index information in categorical plots.
Bug fixes and adaptations#
Fixed the behavior of
PairGridto properly exclude null datapoints from each plot when set to
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
truncate=Falseto progressively expand the x axis limits. Because there are currently limitations on how autoscaling works in matplotlib, the default value for
truncatein seaborn has also been changed to
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
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
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 for
Fixed a bug when passing a
normobject and using color annotations in
Fixed a bug where annotations were not rearranged to match the clustering in
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
Avoided error/warning in
lineplot()when plotting categoricals with empty levels.
colorsto be passed through to a bivariate
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.