Description
<img src="https://raw.githubusercontent.com/mwaskom/seaborn/master/doc/_static/logo-wide-lightbg.svg"><br> -------------------------------------- seaborn: statistical data visualization ======================================= [](https://pypi.org/project/seaborn/) [](https://github.com/mwaskom/seaborn/blob/master/LICENSE.md) [](https://doi.org/10.21105/joss.03021) [](https://github.com/mwaskom/seaborn/actions) [](https://codecov.io/gh/mwaskom/seaborn) Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics. Documentation ------------- Online documentation is available at [seaborn.pydata.org](https://seaborn.pydata.org). The docs include a [tutorial](https://seaborn.pydata.org/tutorial.html), [example gallery](https://seaborn.pydata.org/examples/index.html), [API reference](https://seaborn.pydata.org/api.html), [FAQ](https://seaborn.pydata.org/faq), and other useful information. To build the documentation locally, please refer to [`doc/README.md`](doc/README.md). Dependencies ------------ Seaborn supports Python 3.8+. Installation requires [numpy](https://numpy.org/), [pandas](https://pandas.pydata.org/), and [matplotlib](https://matplotlib.org/). Some advanced statistical functionality requires [scipy](https://www.scipy.org/) and/or [statsmodels](https://www.statsmodels.org/). Installation ------------ The latest stable release (and required dependencies) can be installed from PyPI: pip install seaborn It is also possible to include optional statistical dependencies: pip install seaborn[stats] Seaborn can also be installed with conda: conda install seaborn Note that the main anaconda repository lags PyPI in adding new releases, but conda-forge (`-c conda-forge`) typically updates quickly. Citing ------ A paper describing seaborn has been published in the [Journal of Open Source Software](https://joss.theoj.org/papers/10.21105/joss.03021). The paper provides an introduction to the key features of the library, and it can be used as a citation if seaborn proves integral to a scientific publication. Testing ------- Testing seaborn requires installing additional dependencies; they can be installed with the `dev` extra (e.g., `pip install .[dev]`). To test the code, run `make test` in the source directory. This will exercise the unit tests (using [pytest](https://docs.pytest.org/)) and generate a coverage report. Code style is enforced with `flake8` using the settings in the [`setup.cfg`](./setup.cfg) file. Run `make lint` to check. Alternately, you can use `pre-commit` to automatically run lint checks on any files you are committing: just run `pre-commit install` to set it up, and then commit as usual going forward. Development ----------- Seaborn development takes place on Github: https://github.com/mwaskom/seaborn Please submit bugs that you encounter to the [issue tracker](https://github.com/mwaskom/seaborn/issues) with a reproducible example demonstrating the problem. Questions about usage are more at home on StackOverflow, where there is a [seaborn tag](https://stackoverflow.com/questions/tagged/seaborn).
Release History
| Version | Changes | Urgency | Date |
|---|---|---|---|
| 0.13.2 | Imported from PyPI (0.13.2) | Low | 4/21/2026 |
| v0.13.2 | This is a minor release containing internal changes that adapt to upcoming deprecations in pandas. All users are encouraged to update. | Low | 1/25/2024 |
| v0.13.1 | This is a minor release with some bug fixes and a couple new features. All users are encouraged to update. - |Feature| Added support for weighted mean estimation (with boostrap CIs) in `lineplot`, `barplot`, `pointplot`, and `objects.Est` (#3580, #3586). - |Feature| Added the `extent` option in `objects.Plot.layout` (#3552). - |Fix| Fixed a regression in v0.13.0 that triggered an exception when working with non-numpy data types (#3516). - |Fix| Fixed a bug in `objects.Plot` so that t | Low | 12/31/2023 |
| v0.13.0 | **See the [online docs](https://seaborn.pydata.org/whatsnew/v0.13.0.html) for an annotated version of these notes with working links.** 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](https://www.pola.rs), | Low | 9/29/2023 |
| v0.13.0rc0 | This is a release candidate for seaborn v0.13.0, a major release with a complete overhaul of seaborn's categorical plotting functions. Please test the release candidate, especially the categorical plots. The internals of these functions have been completely rewritten to provide new functionality and to better align with the rest of the library. There are some intentional changes to default behavior / deprecations, but also the potential for unintentional breakage. Please help surface any exam | Low | 9/26/2023 |
| v0.12.2 | v0.12.2 (December 2022) ----------------------- This is an incremental release that is a recommended upgrade for all users. It is very likely the final release of the 0.12 series and the last version to support Python 3.7. - |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 additi | Low | 12/30/2022 |
| v0.12.1 | This is an incremental release that is a recommended upgrade for all users. It addresses a handful of bugs / regressions in v0.12.0 and adds several features and enhancements to the new [objects interface](http://seaborn.pydata.org/tutorial/objects_interface). - 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 | Low | 10/18/2022 |
| v0.12.0 | ## Introduction of the objects interface This release debuts the <span class="title-ref">seaborn.objects</span> 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 suc | Low | 9/6/2022 |
| v0.12.0rc0 | This is the first release candidate for seaborn v0.12, a major update introducing [an entirely new interface](http://seaborn.pydata.org/nextgen/) along with [numerous features, enhancements, and fixes](https://github.com/mwaskom/seaborn/blob/v0.12.0rc0/doc/whatsnew/v0.12.0.rst) for existing functionality. To install for testing, run ``` pip install seaborn==0.12.0rc0 ``` There were several renamings and API changes from the final beta release. See the referenced PRs for more informati | Low | 8/14/2022 |
| v0.12.0b3 | This is the third and final beta release for seaborn v0.12, a major update introducing [an entirely new interface](http://seaborn.pydata.org/nextgen/) along with [numerous features, enhancements, and fixes](https://github.com/mwaskom/seaborn/blob/v0.12.0b0/doc/releases/v0.12.0.txt) for existing functionality. To install for testing, run ``` pip install seaborn==0.12.0b3 ``` Changes from the second beta release: ### Objects interface - Added `Est` stat for aggregating with a flex | Low | 8/4/2022 |
| v0.12.0b2 | This is the second beta release for seaborn v0.12, a major update introducing [an entirely new interface](http://seaborn.pydata.org/nextgen/) along with [numerous features, enhancements, and fixes](https://github.com/mwaskom/seaborn/blob/v0.12.0b0/doc/releases/v0.12.0.txt) for existing functionality. To install for testing, run ``` pip install seaborn==0.12.0b2 ``` Changes from the first beta release: ### Objects interface - Added `Plot.label` method for controlling axis labels/ | Low | 7/14/2022 |
| v0.12.0b1 | This is the first beta release for seaborn v0.12, a major update introducing [an entirely new interface](http://seaborn.pydata.org/nextgen/) along with [numerous features, enhancements, and fixes](https://github.com/mwaskom/seaborn/blob/v0.12.0b0/doc/releases/v0.12.0.txt) for existing functionality. To install for testing, run ``` pip install seaborn==0.12.0b1 ``` Changes from the final alpha release: ### Objects interface - Improve tick label defaults and customization (#2877) | Low | 6/27/2022 |
| v0.12.0a1 | This is the second alpha release for seaborn v0.12, a major release introducing [an entirely new interface](http://seaborn.pydata.org/nextgen/) along with [numerous enhancements and fixes](https://github.com/mwaskom/seaborn/blob/v0.12.0a1/doc/releases/v0.12.0.txt) to existing functionality. To install for testing, run ``` pip install https://github.com/mwaskom/seaborn/archive/refs/tags/v0.12.0a1.tar.gz ``` Changes from the first alpha release: ### Objects interface - Add `Norm` | Low | 6/3/2022 |
| v0.12.0a0 | This is the first alpha for seaborn v0.12.0, a major release that introduces an entirely new interface in the `seaborn.objects` namespace. For more information about the new interface, see the development docs at http://seaborn.pydata.org/nextgen. Please experiment with the alpha version and provide feedback on things that are confusing or don't work, but expect some rough edges and instability. | Low | 5/16/2022 |
| v0.11.2 | This is a minor release that addresses issues in the v0.11 series and adds a small number of targeted enhancements. It is a recommended upgrade for all users. - \|Docs\| A paper describing seaborn has been published in the [Journal of Open Source Software](https://joss.theoj.org/papers/10.21105/joss.03021). The paper serves as an introduction to the library and can be used to cite seaborn if it has been integral to a scientific publication. - \|API\| \|Feature\| In `lmplot`, added a ne | Low | 8/16/2021 |
| v0.11.2.rc0 | This is the first release candidate for seaborn v0.11.2, a backwards-compatible release with bug fixes and targeted enhancements. Please test and report any bugs or changed behavior though GitHub issues. | Low | 8/8/2021 |
| joss_paper | This is a duplicate tag for seaborn v0.11.1. It is being created so that Zenodo will mint a DOI for the repository corresponding to seaborn's JOSS paper. | Low | 3/29/2021 |
| v0.11.1 | This a bug fix release and is a recommended upgrade for all users on v0.11.0. Complete release notes are available on the [seaborn website](http://seaborn.pydata.org/whatsnew.html#v0-11-1-december-2020). | Low | 12/20/2020 |
| v0.11.0 | This is a major release with important new features, enhancements to existing functions, and changes to the library. Highlights include an overhaul and modernization of the distributions plotting functions, more flexible data specification, new colormaps, and better narrative documentation. Complete release notes are available on the [seaborn website](https://seaborn.pydata.org/whatsnew.html). | Low | 9/8/2020 |
| v0.11.0.rc0 | This is the first release candidate for v0.11.0, a major release with several important new features and changes to the library. Highlights of the new version include: - A modernization of the distributions module, with the introduction of [`displot`](https://github.com/mwaskom/seaborn/pull/2157), [`histplot`](https://github.com/mwaskom/seaborn/pull/2125), and [`ecdfplot`](https://github.com/mwaskom/seaborn/pull/2141), a complete rewrite of [`kdeplot`](https://github.com/mwaskom/seaborn/pu | Low | 9/2/2020 |
| v0.10.1 | This is minor release with bug fixes for issues identified since 0.10.0. - Fixed a bug that appeared within the bootstrapping algorithm on 32-bit systems. - Fixed a bug where `regplot` would crash on singleton inputs. Now a crash is avoided and regression estimation/plotting is skipped. - Fixed a bug where `heatmap` would ignore user-specified under/over/bad values when recentering a colormap. - Fixed a bug where `heatmap` would use values from masked cells when | Low | 4/26/2020 |
| v0.10.0 | This is a major update that is being released simultaneously with version 0.9.1. It has all of the same features (and bugs\!) as 0.9.1, but there are important changes to the dependencies. Most notably, all support for Python 2 has now been dropped. Support for Python 3.5 has also been dropped. Seaborn is now strictly compatible with Python 3.6+. Minimally supported versions of the dependent PyData libraries have also been increased, in some cases substantially. While seaborn has tended to | Low | 1/24/2020 |
| v0.9.1 | 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` and `cbar_pos` parameters. Additionally, the default organization and scaling with different figure sizes has been improved. - Added the | Low | 1/24/2020 |
| v0.10.0.rc0 | Release v0.10.0.rc0 | Low | 1/24/2020 |
| v0.9.1.rc0 | First release candidate for v0.9.1 | Low | 1/22/2020 |
| v0.9.0 | v0.9.0 (July 2018) ================== Note: a version of these release notes with working links appears in the [online documentation](http://seaborn.pydata.org/whatsnew.html). This is a major release with several substantial and long-desired new features. There are also updates/modifications to the themes and color palettes that give better consistency with matplotlib 2.0 and some notable API changes. New relational plots -------------------- Three completely new plotting functions | Low | 7/16/2018 |
| v0.8.1 | v0.8.1 (September 2017) ----------------------- - Added a warning in `FacetGrid` when passing a categorical plot function without specifying `order` (or `hue_order` when `hue` is used), which is likely to produce a plot that is incorrect. - Improved compatibility between `FacetGrid` or `PairGrid` and interactive matplotlib backends so that the legend no longer remains inside the figure when using `legend_out=True`. - Changed categorical plot functions with small plot elements to use | Low | 9/3/2017 |
| v0.8.0 | - 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_style`, `set_context`, and `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 | Low | 7/8/2017 |
| v0.7.1 | - Added the ability to put "caps" on the error bars that are drawn by `barplot` or `pointplot` (and, by extension, `factorplot`). Additionally, the line width of the error bars can now be controlled. These changes involve the new parameters `capsize` and `errwidth`. See the [github pull request](https://github.com/mwaskom/seaborn/pull/898) for examples of usage. - Improved the row and column colors display in `clustermap`. It is now possible to pass Pandas objects for these elements and, | Low | 6/5/2016 |
| v0.7.0 | This is a major release from 0.6. The main new feature is swarmplot which implements the beeswarm approach for drawing categorical scatterplots. There are also some performance improvements, bug fixes, and updates for compatibility with new versions of dependencies. - Added the swarmplot function, which draws beeswarm plots. These are categorical scatterplots, similar to those produced by stripplot, but position of the points on the categorical axis is chosen to avoid overlapping points. | Low | 1/25/2016 |
| v0.6.0 | This is a major release from 0.5. The main objective of this release was to unify the API for categorical plots, which means that there are some relatively large API changes in some of the older functions. See below for details of those changes, which may break code written for older versions of seaborn. There are also some new functions (stripplot, and countplot), numerous enhancements to existing functions, and bug fixes. Additionally, the documentation has been completely revamped and expand | Low | 6/29/2015 |
| v0.5.1 | This is a bugfix release that includes a workaround for an issue in matplotlib 1.4.2 and fixes for two bugs in functions that were new in 0.5.0. - Implemented a workaround for a bug in matplotlib 1.4.2 that prevented point markers from being drawn when the seaborn styles had been set. See this [github issue](https://github.com/mwaskom/seaborn/issues/344) for more information. - Fixed a bug in heatmap where the mask was vertically reversed relative to the data. - Fixed a bug in cl | Low | 11/22/2014 |
| v0.5.0 | This is a major release from 0.4. Highlights include new functions for plotting heatmaps, possibly while applying clustering algorithms to discover structured relationships. These functions are complemented by new custom colormap functions and a full set of IPython widgets that allow interactive selection of colormap parameters. The palette tutorial has been rewritten to cover these new tools and more generally provide guidance on how to use color in visualizations. There are also a number of sm | Low | 11/14/2014 |
| v0.4.0 | This is a major release from 0.3. Highlights include new approaches for quick, high-level dataset exploration (along with a more flexible interface and easy creation of perceptually-appropriate color palettes using the cubehelix system. Along with these additions, there are a number of smaller changes that make visualizing data with seaborn easier and more powerful. ## Plotting functions - A new object, PairGrid, and a corresponding function pairplot, for drawing grids of pairwise relations | Low | 9/3/2014 |
| v0.3.1 | This is a minor release from 0.3 with fixes for several bugs. ## Plotting functions - The size of the points in pointplot and factorplot is now scaled with the linewidth for better aesthetics across different plotting contexts. - The pointplot glyphs for different levels of the hue variable are drawn at different z-orders so that they appear uniform. ## Bug Fixes - Fixed a bug in FacetGrid (and thus affecting lmplot and factorplot) that appeared when `col_wrap` was used with a number of facets | Low | 4/21/2014 |
| v0.3.0 | # v0.3.0 (March 2014) This is a major release from 0.2 with a number of enhancements to the plotting capabilities and styles. Highlights include FacetGrid, factorplot, jointplot, and an overhaul to style management. There is also lots of new documentation, including an example gallery and reorganized tutorial. ## New plotting functions - The FacetGrid class adds a new form of functionality to seaborn, providing a way to abstractly structure a grid of plots corresponding to subsets of a d | Low | 3/23/2014 |
| v0.2.1 | This is a bugfix release, with no new features. ## Bug fixes - Changed the mechanics of `violinplot()` and `boxplot()` when using a `Series` object as data and performing a `groupby` to assign data to bins to address a problem that arises in Pandas 0.13. - Additionally fixed the `groupby` code to work with all styles of group specification (specifically, using a dictionary or a function now works). - Fixed a bug where artifacts from the kde fitting could undershoot and create a plot whe | Low | 1/15/2014 |
| v0.2.0 | This is a major release from 0.1 with a number of API changes, enhancements, and bug fixes. Highlights include an overhaul of timeseries plotting to work intelligently with dataframes, the new function `interactplot()` for visualizing continuous interactions, bivariate kernel density estimates in `kdeplot()`, and significant improvements to color palette handling. Version 0.2 also introduces experimental support for Python 3. In addition to the library enhancements, the documentation has been | Low | 12/23/2013 |
Dependencies & License Audit
Loading dependencies...
Similar Packages
azure-core-tracing-opentelemetryMicrosoft Azure Azure Core OpenTelemetry plugin Library for Pythonazure-template_0.1.0b6187637