Seaborn is a library for making statistical graphics in Python. It is built on top of matplotlib and closely integrated with pandas data structures.
Here is some of the functionality that seaborn offers:
A dataset-oriented API for examining relationships between multiple variables
Convenient views onto the overall structure of complex datasets
Specialized support for using categorical variables to show observations or aggregate statistics
Options for visualizing univariate or bivariate distributions and for comparing them between subsets of data
Automatic estimation and plotting of linear regression models for different kinds of dependent variables
High-level abstractions for structuring multi-plot grids that let you easily build complex visualizations
Concise control over matplotlib figure styling with several built-in themes
Tools for choosing color palettes that faithfully reveal patterns in your data
Seaborn aims to make visualization a central part of exploring and understanding data. Its dataset-oriented plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mappings and statistical aggregations to produce informative plots.
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Release files for seaborn 0.11.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| seaborn-0.11.2.tar.gz | 268.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| seaborn-0.11.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 561.7 kB
Release files / seaborn-0.11.2.tar.gz
| Download URL | seaborn-0.11.2.tar.gz |
|---|---|
| Size | 268.8 kB |
| Tags | Source |
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Release files / seaborn-0.11.2-py3-none-any.whl
| Download URL | seaborn-0.11.2-py3-none-any.whl |
|---|---|
| Size | 292.8 kB |
| Tags | Python 3 |
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