Code librarySample
seaborn
Open-source community
A statistical plotting library on top of Matplotlib: one call for distributions, regressions and grouped comparisons from a pandas DataFrame.
Licence
Open source
Built by
Developers
Languages
Python
Runs on
Python code, Jupyter notebooks
Scores
Out of 5. The tick marks the average for code libraries in the library.
- Ease of use
- 4
- Visual control
- 3
- Interactivity
- 1
- Sharing
- 2
- Governance
- 1
- Low cost
- 5
- Data scale
- 3
Strengths
- Statistical charts in one call: KDE, violin, regression and pair plots
- Works directly with tidy pandas DataFrames
- Attractive defaults and colour palettes
Limitations
- Static output only
- Fine tuning still means dropping down to Matplotlib
- Not meant for dashboards
Best for
- Exploratory data analysis in notebooks
- Statistical comparisons between groups
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