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| Name: python313-seaborn | Distribution: openSUSE Tumbleweed |
| Version: 0.13.2 | Vendor: openSUSE |
| Release: 5.2 | Build date: Sat Dec 20 21:03:16 2025 |
| Group: Unspecified | Build host: reproducible |
| Size: 2381127 | Source RPM: python-seaborn-0.13.2-5.2.src.rpm |
| Packager: https://bugs.opensuse.org | |
| Url: https://github.com/mwaskom/seaborn | |
| Summary: Statistical data visualization for python | |
Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. Some of the features that seaborn offers are: - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - Functions that visualize matrices of data and use clustering algorithms to discover structure in those matrices - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations
BSD-2-Clause AND BSD-3-Clause AND MIT
* Sat Dec 20 2025 Ben Greiner <code@bnavigator.de>
- Add seaborn-pr3820-deprecations.patch
* gh#mwaskom/seaborn#3820
* Tue Mar 04 2025 Markéta Machová <mmachova@suse.com>
- Move away from python-fastcluster, dead upstream
* Mon Feb 24 2025 Markéta Machová <mmachova@suse.com>
- Add upstream mpl-tick.patch to support matplotlib 3.10
* Tue Jul 02 2024 Steve Kowalik <steven.kowalik@suse.com>
- Add patch support-numpy-2.patch:
* Remove reference to a now-removed warning.
* Fri Feb 16 2024 Ben Greiner <code@bnavigator.de>
- Update to 0.13.2
* This is a minor release containing internal changes that adapt
to upcoming deprecations in pandas.
- Release 0.13.1
* This is a minor release with some bug fixes and a couple new
features.
* Added support for weighted mean estimation (with boostrap CIs)
in lineplot, barplot, pointplot, and objects.Est (#3580,
[#3586]).
* Added the extent option in objects.Plot.layout (#3552).
* Fixed a regression in v0.13.0 that triggered an exception when
working with non-numpy data types (#3516).
* Fixed a bug in objects.Plot so that tick labels are shown for
wrapped axes that aren't in the bottom-most row (#3600).
* Fixed a bug in catplot where a blank legend would be added when
hue was redundantly assigned (#3540).
* Fixed a bug in catplot where the edgecolor parameter was
ignored with kind="bar" (#3547).
* Fixed a bug in boxplot where an exception was raised when using
the matplotlib bootstrap option (#3562).
* Fixed a bug in lineplot where an exception was raised when hue
was assigned with an empty dataframe (#3569).
* Fixed a bug in multiple categorical plots that raised with
hue=None and dodge=True; this is now has no effect (#3605).
- Release 0.13.0
* This is a major release with a number of important new features
and changes. The highlight is a major overhaul to seaborn's
categorical plotting functions, providing them with many new
capabilities and better aligning their API with the rest of the
library. There is also provisional support for alternate
dataframe libraries like polars, a new theme and display
configuration system for objects.Plot, and many smaller
bugfixes and enhancements.
* Major enhancements to categorical plots
* Support for alternate dataframe libraries
* Improved configuration for the objects interface
* For a complete description see
https://seaborn.pydata.org/whatsnew/v0.13.0.html
- Drop obsolete patches
* inf_as_na.patch
* numpy-1.25.patch
* statsmodels-0.14.patch
* Thu Sep 14 2023 Markéta Machová <mmachova@suse.com>
- Add inf_as_na.patch to fix tests again, this time with pandas
* Tue Aug 08 2023 Daniel Garcia <daniel.garcia@suse.com>
- Skip broken tests in i586
* Tue Aug 08 2023 Daniel Garcia <daniel.garcia@suse.com>
- Add numpy-1.25.patch gh#mwaskom/seaborn#3391
- Add statsmodels-0.14.patch gh#mwaskom/seaborn#3356
* Wed Jan 11 2023 Ben Greiner <code@bnavigator.de>
- Update to 0.12.2
* |Feature| Added the objects.KDE stat (#3111).
* |Feature| Added the objects.Boolean scale (#3205).
* |Enhancement| Improved user feedback for failures during plot
compilation by catching exceptions and re-raising with a
PlotSpecError that provides additional context. (#3203).
* |Fix| Improved calculation of automatic mark widths with
unshared facet axes (#3119).
* |Fix| Improved robustness to empty data in several components
of the objects interface (#3202).
* |Fix| Fixed a bug where legends for numeric variables with
large values would be incorrectly shown (i.e. with a missing
offset or exponent; #3187).
* |Fix| Fixed a regression in v0.12.0 where manually-added labels
could have duplicate legend entries (#3116).
* |Fix| Fixed a bug in histplot with kde=True and log_scale=True
where the curve was not scaled properly (#3173).
* |Fix| Fixed a bug in relplot where inner axis labels would be
shown when axis sharing was disabled (#3180).
* |Fix| Fixed a bug in objects.Continuous to avoid an exception
with boolean data (#3190).
- Release 0.12.1
* Added the objects.Text mark (#3051).
* Added the objects.Dash mark (#3074).
* Added the objects.Perc stat (#3063).
* Added the objects.Count stat (#3086).
* The objects.Band and objects.Range marks will now cover the
full extent of the data if min / max variables are not
explicitly assigned or added in a transform (#3056).
* The objects.Jitter move now applies a small amount of jitter by
default (#3066).
* Axes with a objects.Nominal scale now appear like categorical
axes in classic seaborn, with fixed margins, no grid, and an
inverted y axis (#3069).
* The objects.Continuous.label method now accepts base=None to
override the default formatter with a log transform (#3087).
* Marks that sort along the orient axis (e.g. objects.Line) now
use a stable algorithm (#3064).
* Added a label parameter to pointplot, which addresses a
regression in 0.12.0 when pointplot is passed to FacetGrid
(#3016).
* Fixed a bug that caused an exception when more than two layers
with the same mappings were added to objects.Plot (#3055).
* Made objects.PolyFit robust to missing data (#3010).
* Fixed a bug in objects.Plot that occurred when data assigned to
the orient coordinate had zero variance (#3084).
* Fixed a regression in kdeplot where passing cmap for an
unfilled bivariate plot would raise an exception (#3065).
* Addressed a performance regression in lineplot with a large
number of unique x values (#3081).
* Seaborn no longer contains doctest-style examples, simplifying
the testing infrastructure (#3034).
- Release 0.12.0
[#]# Introduction of the objects interface
* This release debuts the seaborn.objects interface, an entirely
new approach to making plots with seaborn. It is the product of
several years of design and 16 months of implementation work.
The interface aims to provide a more declarative, composable,
and extensible API for making statistical graphics. It is
inspired by Wilkinson's grammar of graphics, offering a
Pythonic API that is informed by the design of libraries such
as ggplot2 and vega-lite along with lessons from the past 10
years of seaborn's development.
* For more information and numerous examples, see the tutorial
chapter and API reference.
* This initial release should be considered "experimental". While
it is stable enough for serious use, there are definitely some
rough edges, and some key features remain to be implemented. It
is possible that breaking changes may occur over the next few
minor releases. Please be patient with any limitations that you
encounter and help the development by reporting issues when you
find behavior surprising.
[#]# Keyword-only arguments
* Seaborn's plotting functions now require explicit keywords for
most arguments, following the deprecation of positional
arguments in v0.11.0. With this enforcement, most functions
have also had their parameter lists rearranged so that data is
the first and only positional argument. This adds consistency
across the various functions in the library. It also means that
calling func(data) will do something for nearly all functions
(those that support wide-form data) and that pandas.DataFrame
can be piped directly into a plot. It is possible that the
signatures will be loosened a bit in future releases so that x
and y can be positional, but minimal support for positional
arguments after this change will reduce the chance of
inadvertent mis-specification (2804).
[#]# Modernization of categorical scatterplots
* This release begins the process of modernizing the categorical
plots, beginning with stripplot and swarmplot. These functions
are sporting some enhancements that alleviate a few
long-running frustrations (2413, 2447):
* The new native_scale parameter allows numeric or datetime
categories to be plotted with their original scale rather than
converted to strings and plotted at fixed intervals.
* The new formatter parameter allows more control over the string
representation of values on the categorical axis. There should
also be improved defaults for some types, such as dates.
* It is now possible to assign hue when using only one coordinate
variable (i.e. only x or y).
* It is now possible to disable the legend.
* The updates also harmonize behavior with functions that have
been more recently introduced. This should be relatively
non-disruptive, although a few defaults will change:
* The functions now hook into matplotlib's unit system for
plotting categorical data. (Seaborn's categorical functions
actually predate support for categorical data in matplotlib.)
This should mostly be transparent to the user, but it may
resolve a few edge cases. For example, matplotlib interactivity
should work better (e.g., for showing the data value under the
cursor).
* A color palette is no longer applied to levels of the
categorical variable by default. It is now necessary to
explicitly assign hue to see multiple colors (i.e., assign the
same variable to x/y and hue). Passing palette without hue will
continue to be honored for one release cycle.
* Numeric hue variables now receive a continuous mapping by
default, using the same rules as scatterplot. Pass
palette="deep" to reproduce previous defaults.
* The plots now follow the default property cycle; i.e. calling
an axes-level function multiple times with the same active axes
will produce different-colored artists.
* Currently, assigning hue and then passing a color will produce
a gradient palette. This is now deprecated, as it is easy to
request a gradient with, e.g. palette="light:blue".
* Similar enhancements / updates should be expected to roll out
to other categorical plotting functions in future releases.
There are also several function-specific enhancements:
* In stripplot, a "strip" with a single observation will be
plotted without jitter (2413)
* In swarmplot, the points are now swarmed at draw time, meaning
that the plot will adapt to further changes in axis scaling or
tweaks to the plot layout (2443).
* In swarmplot, the proportion of points that must overlap before
issuing a warning can now be controlled with the warn_thresh
parameter (2447).
* In swarmplot, the order of the points in each swarm now matches
the order in the original dataset; previously they were sorted.
This affects only the underlying data stored in the matplotlib
artist, not the visual representation (2443).
[#]# More flexible errorbars
* Increased the flexibility of what can be shown by the
internally-calculated errorbars for lineplot, barplot, and
pointplot.
* With the new errorbar parameter, it is now possible to select
bootstrap confidence intervals, percentile / predictive
intervals, or intervals formed by scaled standard deviations or
standard errors. The parameter also accepts an arbitrary
function that maps from a vector to an interval. There is a new
user guide chapter demonstrating these options and explaining
when you might want to use each one.
* As a consequence of this change, the ci parameter has been
deprecated. Note that regplot retains the previous API, but it
will likely be updated in a future release (2407, 2866).
[#]# Other updates
* It is now possible to aggregate / sort a lineplot along the y
axis using orient="y" (2854).
* Made it easier to customize FacetGrid / PairGrid / JointGrid
with a fluent (method-chained) style by adding apply/ pipe
methods. Additionally, fixed the tight_layout and refline
methods so that they return self (2926).
* Added FacetGrid.tick_params and PairGrid.tick_params to
customize the appearance of the ticks, tick labels, and
gridlines of all subplots at once (2944).
* Added a width parameter to barplot (2860).
* It is now possible to specify estimator as a string in barplot
and pointplot, in addition to a callable (2866).
* Error bars in regplot now inherit the alpha value of the points
they correspond to (2540).
* When using pairplot with corner=True and diag_kind=None, the
top left y axis label is no longer hidden (2850).
* It is now possible to plot a discrete histplot as a step
function or polygon (2859).
* It is now possible to customize the appearance of elements in a
boxenplot with box_kws/line_kws/flier_kws (2909).
* Improved integration with the matplotlib color cycle in most
axes-level functions (2449).
* Fixed a regression in 0.11.2 that caused some functions to
stall indefinitely or raise when the input data had a duplicate
index (2776).
* Fixed a bug in histplot and kdeplot where weights were not
factored into the normalization (2812).
* Fixed two edgecases in histplot when only binwidth was provided
(2813).
* Fixed a bug in violinplot where inner boxes/points could be
missing with unpaired split violins (2814).
* Fixed a bug in PairGrid where an error would be raised when
defining hue only in the mapping methods (2847).
* Fixed a bug in scatterplot where an error would be raised when
hue_order was a subset of the hue levels (2848).
* Fixed a bug in histplot where dodged bars would have different
widths on a log scale (2849).
* In lineplot, allowed the dashes keyword to set the style of a
line without mapping a style variable (2449).
* Improved support in relplot for "wide" data and for faceting
variables passed as non-pandas objects (2846).
* Subplot titles will no longer be reset when calling
FacetGrid.map or FacetGrid.map_dataframe (2705).
* Added a workaround for a matplotlib issue that caused
figure-level functions to freeze when plt.show was called
(2925).
* Improved robustness to numerical errors in kdeplot (2862).
* Fixed a bug where rugplot was ignoring expand_margins=False
(2953).
* The patch.facecolor rc param is no longer set by set_palette
(or set_theme). This should have no general effect, because the
matplotlib default is now "C0" (2906).
* Made scipy an optional dependency and added <span class="...
- Move to PEP517 build with flit-core
- Drop seaborn-pr2562-clustermap-colors.patch
* Mon Nov 14 2022 pgajdos@suse.com
- python-six is not required
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