An R interface to Apache ECharts for creating interactive charts and visualizations.
echarts4r is an R package that provides a complete interface to Apache ECharts, allowing R users to create interactive, publication-quality data visualizations directly from their R code. It solves the problem of integrating advanced JavaScript charting libraries into R workflows by providing an intuitive R syntax wrapper around ECharts' extensive capabilities.
R developers, data scientists, and analysts who need to create interactive visualizations for reports, dashboards, or Shiny applications without leaving the R ecosystem.
Developers choose echarts4r because it combines R's data manipulation strengths with ECharts' powerful visualization engine through a clean, pipe-friendly API, eliminating the need to write JavaScript while producing professional, interactive charts.
🐳 ECharts 5 for R
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Provides complete interface to Apache ECharts version 6, enabling advanced interactive features like zoom and dynamic tooltips directly from R syntax, as highlighted in the README's feature list.
Seamlessly embeds interactive charts in Shiny web applications, making it ideal for building dashboards without writing JavaScript, as specified in the key features.
Designed to work with R's pipe operator for clean, readable code, as demonstrated in the basic example using e_chart and e_scatter with piping.
Supports a wide range of chart types including scatter plots, line charts, bar charts, and maps, leveraging ECharts' comprehensive visualization library for diverse data needs.
The README warns of a recent change from ECharts 4 to 6 on Github, indicating potential breaking changes and instability in the development version, which could affect production use.
Relies on Apache ECharts, introducing external JavaScript library dependencies that increase bundle size and may cause compatibility issues in some deployment environments.
While it abstracts JavaScript, users must still understand ECharts' extensive configuration options, which can be overwhelming compared to simpler, native R visualization packages.