Seaborn
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Superset | 54,289 |  | 16 | 18 hours ago | 6 | April 18, 2023 | 1,508 | apache-2.0 | TypeScript | |
| Apache Superset is a Data Visualization and Data Exploration Platform | ||||||||||
| Excelize | 15,975 | 357 | 6 days ago | 186 | April 09, 2023 | 89 | bsd-3-clause | Go | ||
| Go language library for reading and writing Microsoft Excel™ (XLAM / XLSM / XLSX / XLTM / XLTX) spreadsheets | ||||||||||
| Seaborn | 11,162 | | 6,393 | 4,230 | a day ago | 33 | February 02, 2023 | 118 | bsd-3-clause | Python |
| Statistical data visualization in Python | ||||||||||
| Vaex | 7,985 |  | 2 | 26 | 22 days ago | 69 | July 21, 2023 | 504 | mit | Python |
| Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀 | ||||||||||
| Roughviz | 6,520 |  | 3 | 5 | 3 days ago | 7 | March 28, 2020 | 16 | mit | JavaScript |
| Reusable JavaScript library for creating sketchy/hand-drawn styled charts in the browser. | ||||||||||
| Smile | 5,793 | 121 | 34 | a month ago | 33 | June 14, 2023 | 17 | other | Java | |
| Statistical Machine Intelligence & Learning Engine | ||||||||||
| Lux | 4,642 |  | 2 | 2 months ago | 18 | February 19, 2022 | 81 | apache-2.0 | Python | |
| Automatically visualize your pandas dataframe via a single print! 📊 💡 | ||||||||||
| Orange3 | 4,257 |  | 57 | 42 | 4 days ago | 60 | December 13, 2022 | 88 | other | Python |
| 🍊 :bar_chart: :bulb: Orange: Interactive data analysis | ||||||||||
| Dtale | 4,239 |  | 17 | 12 days ago | 171 | July 19, 2023 | 50 | lgpl-2.1 | TypeScript | |
| Visualizer for pandas data structures | ||||||||||
| Aim | 4,233 | 19 hours ago | 172 | October 11, 2021 | 310 | apache-2.0 | Python | |||
| Aim 💫 — An easy-to-use & supercharged open-source AI metadata tracker (experiment tracking, AI agents tracing) | ||||||||||
seaborn: statistical data visualization
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.
The docs include a tutorial, example gallery, API reference, FAQ, and other useful information.
To build the documentation locally, please refer to doc/README.md.
Dependencies
Seaborn supports Python 3.8+.
Installation requires numpy, pandas, and matplotlib. Some advanced statistical functionality requires scipy and/or statsmodels.
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. 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) and generate a coverage report.
Code style is enforced with flake8 using the settings in the 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: mwaskom/seaborn
Please submit bugs that you encounter to the issue tracker with a reproducible example demonstrating the problem. Questions about usage are more at home on StackOverflow, where there is a seaborn tag.
