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tidyverse/ggplot2

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6,948 estrellas·2,131 forks·R·4 vistasggplot2.tidyverse.org↗

Ggplot2

ggplot2 is a data visualization library for R based on a formal grammar of graphics. It provides a declarative plotting framework that allows users to create complex graphics by combining geometric objects, statistical summaries, and coordinate systems.

The system is distinguished by a layered approach to composition, where visualizations are built incrementally by stacking independent geometric, statistical, and coordinate layers. It utilizes a hierarchical styling engine to manage non-data elements such as backgrounds, fonts, and margins, and includes a multi-panel faceting tool for splitting data into a grid of small multiple plots based on discrete variables.

The library covers broad capability areas including aesthetic data mapping, statistical transformations for calculating bins and densities, and coordinate space projection for Cartesian, polar, and geospatial layouts. It also provides tools for element position adjustment to prevent overlap, visual guide configuration for axes and legends, and utilities for exporting high-resolution raster images or multi-page documents.

Features

  • Layered Visualization Composition - Employs a layered approach to build visualizations by stacking geometric objects, scales, and facet specifications.
  • Declarative Visualization Grammars - Implements a formal grammar-based declarative paradigm for constructing complex data visualizations.
  • Statistical Transformation Pipelines - Computes summary statistics, bins, and densities on-the-fly during the rendering process.
  • Statistical Analysis - Visualizes statistical trends by computing derived values such as bins, densities, and contours from raw data.
  • Charts and Visualization - Provides a comprehensive framework for rendering charts and visualizations with detailed control over axes and legends.
  • R Visualization - Serves as a primary library for statistical graphics and interactive data analysis within the R environment.
  • Hierarchical Chart Themes - Modifies non-data elements like backgrounds and fonts using a nested, hierarchical styling system.
  • Faceted Plotting Systems - Provides structural logic for partitioning data into multi-panel layouts across rows and columns.
  • Grid Composition Tools - Implements a system for arranging multiple subplots in structured grids for side-by-side comparative analysis.
  • Incremental Composition - Adds geometric objects, scales, and coordinate systems incrementally to build sophisticated final visualizations.
  • Exploratory Data Analysis - Enables discovery of patterns and statistical insights through the creation of layered plots and faceted grids.
  • Chart Composition Layers - Builds visualizations by incrementally stacking independent geometric, statistical, and coordinate layers.
  • Geometric Data Mappings - Maps dataset variables to geometric shapes and visual properties like color and size.
  • Data Visualization Scales - Provides mapping functions that translate abstract data domains into visual ranges like colors and coordinates.
  • Faceted Plotting - Provides a multi-panel faceting tool for splitting data into a grid of small multiple plots.
  • Declarative Statistical Plotting - Uses declarative syntax to map data to graphical marks for statistical charts with automated scales.
  • Plot - Utilizes a hierarchical styling engine to manage backgrounds, fonts, and margins independently of the data.
  • Plot Axis Customizers - Offers tools for configuring labels, scales, and ticks on coordinate systems to improve chart clarity.
  • Legend Management - Manages the positioning and symbols used in legends to explain the mapping of data to aesthetics.
  • Visualization Coordinate Mapping - Defines how data values are translated to visual coordinates for various chart layouts.
  • Geographic Data Mapping - Renders geographic shapes and maps data points onto spatial coordinate systems for regional analysis.
  • Geospatial Rendering Engines - Converts geographic coordinates and spatial data into visual renderable layers.
  • Plot Annotations - Provides tools to add text and geometric shapes to specific plot coordinates for highlighting key information.
  • Scientific Figure Generation - Provides precise control over themes, axes, and legends to generate high-resolution figures for scientific reports.
  • Coordinate Projections - Implements mathematical utilities for calculating scales and projections for visual mapping across various coordinate systems.
  • Visual Overlap Adjustments - Shifts overlapping points using dodging, nudging, or jittering to make crowded data more visible.
  • Styling Architectures - Utilizes a hierarchical styling engine to manage non-data elements through a system of nested style overrides.
  • Visualization and Analysis - Grammar of graphics implementation for statistical data visualization.
  • Data Processing and Analytics - Implementation of the grammar of graphics for data visualization.

Historial de estrellas

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Ver las 30 alternativas a Ggplot2→

Preguntas frecuentes

¿Qué hace tidyverse/ggplot2?

ggplot2 is a data visualization library for R based on a formal grammar of graphics. It provides a declarative plotting framework that allows users to create complex graphics by combining geometric objects, statistical summaries, and coordinate systems.

¿Cuáles son las características principales de tidyverse/ggplot2?

Las características principales de tidyverse/ggplot2 son: Layered Visualization Composition, Declarative Visualization Grammars, Statistical Transformation Pipelines, Statistical Analysis, Charts and Visualization, R Visualization, Hierarchical Chart Themes, Faceted Plotting Systems.

¿Qué alternativas de código abierto existen para tidyverse/ggplot2?

Las alternativas de código abierto para tidyverse/ggplot2 incluyen: has2k1/plotnine — Plotnine is a data visualization library for Python based on the Grammar of Graphics. It serves as a declarative… hadley/ggplot2 — ggplot2 is an R data visualization library and statistical graphics engine. It implements a grammar of graphics that… observablehq/plot — This is a grammar of graphics visualization library used to build charts by mapping tabular data to visual marks. It… mwaskom/seaborn — Seaborn is a Python library designed for statistical data visualization. It functions as a high-level interface built… yhat/ggpy — ggpy is a Python library for statistical data visualization based on the grammar of graphics. It functions as a… bqplot/bqplot — bqplot is an interactive data visualization library for IPython and Jupyter notebooks that utilizes a grammar of…