seaborn: statistical data visualization
Here is some of the functionality that seaborn offers:
A dataset-oriented API for examining relationships between multiple variables
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 dependent variables
Convenient views onto the overall structure of complex datasets
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 mapping and statistical aggregation to produce informative plots.
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