graph LR
Core_Plotting_Framework["Core Plotting Framework"]
Statistical_Backend["Statistical Backend"]
Color_Style_Management["Color & Style Management"]
General_Utilities["General Utilities"]
Runtime_Configuration["Runtime Configuration"]
Multi_Plot_Grid_System["Multi-Plot Grid System"]
High_Level_Plotting_API["High-Level Plotting API"]
Interactive_Widgets["Interactive Widgets"]
Core_Plotting_Framework -- "uses" --> Color_Style_Management
Core_Plotting_Framework -- "depends on" --> General_Utilities
Core_Plotting_Framework -- "utilizes" --> Statistical_Backend
Core_Plotting_Framework -- "is influenced by" --> Runtime_Configuration
Statistical_Backend -- "is utilized by" --> Core_Plotting_Framework
Statistical_Backend -- "is utilized by" --> High_Level_Plotting_API
Color_Style_Management -- "is used by" --> Core_Plotting_Framework
Color_Style_Management -- "is used by" --> High_Level_Plotting_API
Color_Style_Management -- "is used by" --> Interactive_Widgets
General_Utilities -- "depends on" --> Color_Style_Management
General_Utilities -- "is depended on by" --> Core_Plotting_Framework
General_Utilities -- "is depended on by" --> High_Level_Plotting_API
General_Utilities -- "is depended on by" --> Multi_Plot_Grid_System
Runtime_Configuration -- "influences" --> Core_Plotting_Framework
Runtime_Configuration -- "interacts with" --> Interactive_Widgets
Multi_Plot_Grid_System -- "builds upon" --> Core_Plotting_Framework
Multi_Plot_Grid_System -- "depends on" --> General_Utilities
Multi_Plot_Grid_System -- "uses" --> Color_Style_Management
Multi_Plot_Grid_System -- "orchestrates" --> High_Level_Plotting_API
High_Level_Plotting_API -- "builds upon" --> Core_Plotting_Framework
High_Level_Plotting_API -- "utilizes" --> Statistical_Backend
High_Level_Plotting_API -- "depends on" --> General_Utilities
High_Level_Plotting_API -- "uses" --> Color_Style_Management
High_Level_Plotting_API -- "is orchestrated by" --> Multi_Plot_Grid_System
Interactive_Widgets -- "uses" --> Color_Style_Management
Interactive_Widgets -- "interacts with" --> Runtime_Configuration
Interactive_Widgets -- "uses" --> High_Level_Plotting_API
click Core_Plotting_Framework href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/seaborn/Core Plotting Framework.md" "Details"
click Statistical_Backend href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/seaborn/Statistical Backend.md" "Details"
click Color_Style_Management href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/seaborn/Color & Style Management.md" "Details"
click General_Utilities href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/seaborn/General Utilities.md" "Details"
click Runtime_Configuration href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/seaborn/Runtime Configuration.md" "Details"
click Multi_Plot_Grid_System href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/seaborn/Multi-Plot Grid System.md" "Details"
click High_Level_Plotting_API href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/seaborn/High-Level Plotting API.md" "Details"
click Interactive_Widgets href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/seaborn/Interactive Widgets.md" "Details"
The seaborn library provides a high-level API for drawing attractive and informative statistical graphics in Python. Its architecture is built around a Core Plotting Framework that handles the fundamental aspects of plot rendering, supported by a Statistical Backend for data analysis and Color & Style Management for aesthetics. General Utilities provide common helper functions, while Runtime Configuration allows global aesthetic adjustments. The High-Level Plotting API offers user-friendly functions for various plot types, often orchestrated by the Multi-Plot Grid System for complex layouts. Interactive Widgets provide dynamic control over certain aspects, primarily color palettes.
The foundational layer of seaborn's plotting capabilities, responsible for handling data input, variable mapping (hue, size, style), axis scaling, managing plot element properties, data grouping, and orchestrating the overall rendering process of visual marks. It provides the VectorPlotter and SemanticMapping classes.
Related Classes/Methods:
seaborn.seaborn._base(full file reference)seaborn.seaborn._core.plot(full file reference)seaborn.seaborn._core.data(full file reference)seaborn.seaborn._core.scales(full file reference)seaborn.seaborn._core.properties(full file reference)seaborn.seaborn._core.rules(full file reference)seaborn.seaborn._core.groupby(full file reference)seaborn.seaborn._core.moves(full file reference)seaborn.seaborn._core.subplots(full file reference)seaborn.seaborn._core.exceptions(full file reference)seaborn.seaborn._marks.area(full file reference)seaborn.seaborn._marks.bar(full file reference)seaborn.seaborn._marks.base(full file reference)seaborn.seaborn._marks.dot(full file reference)seaborn.seaborn._marks.line(full file reference)seaborn.seaborn._marks.text(full file reference)
Provides core statistical algorithms for data aggregation, density estimation (KDE), histogram binning, and empirical cumulative distribution functions (ECDF), serving as the analytical foundation for many seaborn plots.
Related Classes/Methods:
seaborn.seaborn._statistics(full file reference)seaborn.seaborn._stats.aggregation(full file reference)seaborn.seaborn._stats.counting(full file reference)seaborn.seaborn._stats.density(full file reference)seaborn.seaborn._stats.order(full file reference)seaborn.seaborn.algorithms(full file reference)seaborn.seaborn.external.kde(full file reference)
Manages the generation and application of color palettes, including various color space conversions (e.g., HUSL), and provides utilities for generating unique marker and dash styles to ensure visually appealing and informative data representations.
Related Classes/Methods:
seaborn.seaborn.palettes(full file reference)seaborn.seaborn.external.husl(full file reference)
A comprehensive collection of helper functions supporting various aspects of the library, such as argument validation, data manipulation, version compatibility checks, and legend adjustments.
Related Classes/Methods:
seaborn.seaborn.utils(full file reference)seaborn.seaborn._compat(full file reference)seaborn.seaborn.external.appdirs(full file reference)seaborn.seaborn.external.version(full file reference)
Controls the global aesthetic settings of matplotlib, allowing users to apply predefined or custom themes, styles, and plotting contexts to influence the visual appearance of all seaborn plots.
Related Classes/Methods:
seaborn.seaborn.rcmod(full file reference)
Facilitates the creation of complex grids of plots, including facet grids, pair plots, and joint plots, enabling the visualization of relationships across multiple variables or subsets of data with shared axes and consistent aesthetics.
Related Classes/Methods:
seaborn.seaborn.axisgrid(full file reference)
Provides a diverse set of user-facing functions for creating various statistical visualizations, including distribution plots (histograms, KDEs), categorical plots (box, violin, bar), relational plots (scatter, line), regression plots, and matrix plots (heatmaps, cluster maps). These functions abstract away the underlying plotting complexities.
Related Classes/Methods:
seaborn.seaborn.distributions(full file reference)seaborn.seaborn.categorical(full file reference)seaborn.seaborn.relational(full file reference)seaborn.seaborn.regression(full file reference)seaborn.seaborn.matrix(full file reference)
Offers interactive user interface elements, primarily for dynamic selection and preview of color palettes within an interactive Python environment.
Related Classes/Methods:
seaborn.seaborn.widgets(full file reference)