Software Open Access
Michael Waskom; Olga Botvinnik; Drew O'Kane; Paul Hobson; Saulius Lukauskas; David C Gemperline; Tom Augspurger; Yaroslav Halchenko; John B. Cole; Jordi Warmenhoven; Julian de Ruiter; Stephan Hoyer; Jake Vanderplas; Santi Villalba; Gero Kunter; Eric Quintero; Pete Bachant; Marcel Martin; Kyle Meyer; Alistair Miles; Yoav Ram; Cameron Pye; Tal Yarkoni; Mike Lee Williams; Constantine Evans; Clark Fitzgerald; Brian; Chris Fonnesbeck; Antony Lee; Adel Qalieh
v0.8.0 (July 2017)
The default style is no longer applied when seaborn is imported. It is now necessary to explicitly call
set or one or more of
set_palette. Correspondingly, the
seaborn.apionly module has been deprecated.
Changed the behavior of
heatmap (and by extension
clustermap) when plotting divergent dataesets (i.e. when the
center parameter is used). Instead of extending the lower and upper limits of the colormap to be symettrical around the
center value, the colormap is modified so that its middle color corresponds to
center. This means that the full range of the colormap will not be used (unless the data or specified
vmax are symettric), but the upper and lower limits of the colorbar will correspond to the range of the data. See the Github pull request (#1184) for examples of the behavior.
Removed automatic detection of diverging data in
heatmap (and by extension
clustermap). If you want the colormap to be treated as diverging (see above), it is now necessary to specify the
center value. When no colormap is specified, specifying
center will still change the default to be one that is more appropriate for displaying diverging data.
Added four new colormaps, created using viscm for perceptual uniformity. The new colormaps include two sequential colormaps (
"mako") and two diverging colormaps (
"vlag"). These colormaps are registered with matplotlib on seaborn input and the colormap objects can be accessed in the
Changed the default
heatmap colormaps to be
"rocket" (in the case of sequential data) or
"icefire" (in the case of diverging data). Note that this change reverses the direction of the luminance ramp from the previous defaults. While potentially confusing and disruptive, this change better aligns the seaborn defaults with the new matplotlib default colormap (
"viridis") and arguably better aligns the semantics of a "heat" map with the appearance of the colormap.
"auto" as a (default) option for tick labels in
clustermap. This will try to estimate how many ticks can be labeled without the text objects overlapping, which should improve performance for larger matrices.
dodge parameter to boxplot, violinplot, and barplot to allow use of
hue without changing the position or width of the plot elements, as when the
hue varible is not nested within the main categorical variable.
split parameter for stripplot and swarmplot has been renamed to
dodge for consistency with the other categorical functions (and for differentiation from the meaning of
split in violinplot).
Added the ability to draw a colorbar for a bivariate kdeplot with the
cbar parameter (and related
Added the ability to use error bars to show standard deviations rather than bootstrap confidence intervals in most statistical functions by putting
Allow side-specific offsets in
Figure size is no longer part of the seaborn plotting context parameters.
Put a cap on the number of bins used in
type=="hex" to avoid hanging when the reference rule prescribes too many.
Turn off dendrogram axes in
clustermap rather than setting the background color to white.
New matplotlib qualitative palettes (e.g.
"tab10") are now handled correctly.
Some modules and functions have been internally reorganized; there should be no effect on code that uses the
Added a deprecation warning to
tsplot function to indicate that it will be removed or replaced with a substantially altered version in a future release.
coefplot functions are officially deprecated and will be removed in a future release.