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observablehq/plot

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5,305 stars·228 forks·HTML·ISC·4 vuesobservablehq.com/plot↗

Plot

Il s'agit d'une bibliothèque de visualisation de grammaire graphique utilisée pour construire des graphiques en mappant des données tabulaires vers des marques visuelles. Elle fonctionne comme un outil de visualisation de données SVG et une API d'analyse exploratoire des données, permettant aux utilisateurs de rendre des visualisations complexes et des cartes géographiques.

La bibliothèque dispose d'un moteur de rendu de carte GeoJSON qui projette des coordonnées sphériques dans un espace pixel bidimensionnel et d'une interface de visualisation Apache Arrow pour un traitement de données à haute efficacité.

Sa surface de capacités couvre la transformation des données via le binning et le regroupement, l'encodage visuel via l'inférence automatique d'échelle et l'application de schémas de couleurs, ainsi que la génération de multiples petits graphiques (small multiples). Elle prend en charge le rendu de formes géométriques dans des vues en couches et l'exportation d'images statiques dans des environnements côté serveur.

Features

  • Layered Visualization Composition - Implements a layered grammar of graphics to compose independent data, mark, and scale layers into a coherent view.
  • Declarative Visualization Grammars - Implements a formal grammar of graphics that builds charts by layering geometric shapes and mapping data to visual channels.
  • Apache Arrow Processing - Processes diverse input structures, including high-efficiency Apache Arrow tables, for optimized data visualization.
  • Data Visualization - Transforms rows of tabular data into visual representations to accelerate exploratory data analysis.
  • Visual Channel Bindings - Binds data columns and accessor functions to visual mark options to vary attributes across different data points.
  • Exploratory Data Analysis - Provides an API for rapidly transforming tabular data into charts to discover patterns and statistical insights.
  • Exploratory Analysis APIs - Offers a specialized API for rapid data exploration through automated scales, transforms, and small multiples.
  • Scale and Guide Inference Engines - Automatically infers appropriate quantitative, ordinal, and binned scales from data to generate axes and legends.
  • Tabular Data Analysis - Processes tabular data through binning, grouping, and stacking to prepare it for visual representation.
  • In-Memory Format Support - Handles diverse data structures, including arrays of objects and Apache Arrow tables, to improve processing efficiency.
  • Tabular Data Transformations - Computes binned, grouped, or stacked values during the rendering pipeline to prepare raw data for visual representation.
  • Geometric Data Mappings - Renders data as a variety of geometric marks, such as dots, lines, bars, and areas, to represent tabular information.
  • Grammar of Graphics Renderers - Renders tabular data using a grammar of graphics approach to build charts from layered geometric shapes.
  • Data-Driven Shape Generators - Translates tabular records into geometric shapes by binding data columns to visual channels like position and color.
  • SVG Data Visualization - Renders complex data visualizations and geographic maps as scalable vector graphics for web browsers.
  • Data Visualization Scales - Maps abstract data domains to visual properties like position and color through a system of automated scales.
  • Coordinate Projections - Provides mathematical utilities to project spherical longitude and latitude coordinates into two-dimensional pixel positions.
  • Categorical Data Mappings - Assigns discrete, ordinal, or nominal data to uniform visual intervals to prevent interpolation on chart axes.
  • Color Schemes - Encodes data magnitudes and categories using sequential, diverging, or categorical color palettes.
  • Tabular Data Pre-processing - Derives new data values on-the-fly through operations like binning and rolling averages to prepare data for visualization.
  • GeoJSON Renderers - Renders geographic features using the GeoJSON specification and projects them into visual map space.
  • Composable Mark Extensions - Allows creation of specialized chart types by combining primitive geometric marks or adding custom drawing logic.
  • Geographic Projections - Uses mathematical projections to transform spherical longitude and latitude into two-dimensional pixel space.
  • Geographic Data Mapping - Projects geographic coordinates and GeoJSON objects into visual maps to represent spatial trends.
  • Data Transformation Functions - Allows the definition of user-specified functions to derive custom data, indexes, or channels before rendering.
  • Server-Side Chart Image Exports - Produces SVG or PNG representations of visualizations in server-side environments by serializing the plot output.
  • Display Data Transformations - Groups, bins, or stacks data points to resolve overplotting and highlight patterns before rendering visual marks.
  • Small Multiples Generation - Partitions data by categorical or ordinal values to repeat a plot across multiple sub-grids for direct comparison.
  • Small Multiples Visualizations - Creates grids of similar charts to enable direct comparison between different categories or subsets of data.
  • Standalone Scale Generation - Generates independent scale objects that can be reused across different visualizations to maintain consistent mapping.

Historique des stars

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Questions fréquentes

Que fait observablehq/plot ?

Il s'agit d'une bibliothèque de visualisation de grammaire graphique utilisée pour construire des graphiques en mappant des données tabulaires vers des marques visuelles. Elle fonctionne comme un outil de visualisation de données SVG et une API d'analyse exploratoire des données, permettant aux utilisateurs de rendre des visualisations complexes et des cartes géographiques.

Quelles sont les fonctionnalités principales de observablehq/plot ?

Les fonctionnalités principales de observablehq/plot sont : Layered Visualization Composition, Declarative Visualization Grammars, Apache Arrow Processing, Data Visualization, Visual Channel Bindings, Exploratory Data Analysis, Exploratory Analysis APIs, Scale and Guide Inference Engines.

Quelles sont les alternatives open-source à observablehq/plot ?

Les alternatives open-source à observablehq/plot incluent : has2k1/plotnine — Plotnine is a data visualization library for Python based on the Grammar of Graphics. It serves as a declarative… tidyverse/ggplot2 — ggplot2 is a data visualization library for R based on a formal grammar of graphics. It provides a declarative… makieorg/makie.jl — Makie.jl is a high-performance Julia data visualization library and hardware-accelerated plotting engine used to… bqplot/bqplot — bqplot is an interactive data visualization library for IPython and Jupyter notebooks that utilizes a grammar of… yhat/ggpy — ggpy is a Python library for statistical data visualization based on the grammar of graphics. It functions as a… vega/vega-lite — Vega-Lite is a high-level declarative language for specifying interactive, multi-view visualizations. It compiles a…

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