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Overview
This Python statistical visualization library is built on Matplotlib. It accepts variable names from pandas-style tabular data to compare relationships, distributions, and categories, and can map columns to color, shape, size, and faceted panels.
Features and best fit
Based on official documentation; not hands-on tested · Content checked:
Key features
Map data columns to visual properties and faceted panels
Variables can be assigned to the x and y axes as well as color, marker shape, and size. Figure-level functions such as relplot, displot, and catplot can also split data into panels by row or column values.
Sources: [2]
Best fit
Before adoption
Official sources
- [1]seaborn v0.13.2 README(2026-10-04)
- [2]seaborn v0.13.2 introductory tutorial source(2026-10-04)
- [3]seaborn v0.13.2 package metadata(2026-10-04)
- [4]seaborn v0.13.2 release(2026-10-04)
- [5]seaborn v0.13.2 license(2026-10-04)
Supplemental curator note
Its concise interface makes it easy to add comparison dimensions during exploration, but final figures still need a review of statistical assumptions and missing-data handling. Compare it with direct Matplotlib use when fine-grained control is the priority.
Try it in 3 steps
- 1
Install v0.13.2 in a virtual environment
Keep the demo separate from other Python environments and install the reviewed version with its required dependencies.
mkdir -p seaborn-demo && cd seaborn-demo && python3 -m venv .venv && ./.venv/bin/python -m pip install "seaborn==0.13.2" - 2
Create a bar plot from tabular sample data
Save a short script that maps column names to axes without downloading external data.
printf '%s\n' "import matplotlib; matplotlib.use('Agg')" "import pandas as pd" "import seaborn as sns" "data = pd.DataFrame({'day': ['Mon', 'Tue', 'Wed'], 'requests': [120, 175, 150]})" "sns.set_theme()" "plot = sns.barplot(data=data, x='day', y='requests')" "plot.figure.savefig('requests.png', bbox_inches='tight')" > plot.py - 3
Verify the generated image
Run without a display and confirm that requests.png exists and is not empty.
./.venv/bin/python plot.py && test -s requests.png && printf '%s\n' 'created requests.png'
Growth
Growth trends · Last 30 days
14,056 Stars
Trend data is still being collected.
Development activity
Last 90 days · weekly
- Commits (last 30 days)
- 0
- Open PRs
- 61
Development activity is still being collected.
Built with
Categories and tags
Categories
GitHub data
GitHub dataView detailed GitHub data
GitHub Topics
- python
- data-visualization
- data-science
- matplotlib
- pandas
- Stars
- 14,056
- Forks
- 2,142
- Watchers
- 252
- Open issues
- 177
- Contributors
- 217
- Owner type
- User
- Primary language
- Python
- License
- BSD-3-Clause
- Repository last updated
- Jul 6, 2026
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