Intro

Author: dicook

DynamicVisualizations.html

@@ -7,14 +7,15 @@ version: 2024-03-12
 source: https://github.com/cran-task-views/DynamicVisualizations/
 ---
 
-One of the strengths of R is the wealth of data plotting packages. This CRAN Task View maintains a list of dynamic graphics packages, for making animations and interactive plots.
+The wealth of graphics packages in R makes it easy to plot data, models and create conceptual illustrations. This CRAN Task View maintains a list of the dynamic graphics packages, for making animations and interactive plots.
 
-Static plots are not within the scope of this CRAN Task View, neither are graphic devices. Domain-specific packages with only one or two functions to produce interactive plots or animation may not be included. 
+Static plots are not within the scope of this CRAN Task View, neither are graphics devices. Some packages that include only one or two functions to produce interactive plots or animations but are mostly focused on modeling methods or applications are mostly not included. 
 
-If you think that a package is missing from this list, please let us know through issues or pull requests in the [GitHub repository](https://github.com/cran-task-views/DynamicVisualizations).
+If you think that a package is missing from this list, you can post an issue or directly add using a pull request in the [GitHub repository](https://github.com/cran-task-views/DynamicVisualizations).
 
-Dynamic visualizations offers the flexibility for users to interact with the plot. This can be useful to query additional details, such as mouse-over to access additional information using tooltips or pop-ups. In the context of exploratory data analysis, this means to view the data across multiple plots through highlighting (brushing). In R, dynamic visualizations are generated by either rendering successive frames in the plot window or interfacing with Javascript libraries through widgets. These packages can be grouped into general purpose packages and those designed for specific applications, such as maps and networks, or for particular plot types, such as parallel coordinate plots.
+Dynamic visualizations include interactive graphics which offer the flexibility for users to interact with the plot, with mouse or cursor selection, for example. This can be useful to query additional details, such as using mouse-over to provide additional information about a point or line in the plot. For exploratory data analysis, it is beneficial to view and link multiple plots using highlighting or brushing. Most interactivity is provided by interfacing R with external libraries like Javascript. Dynamic visualizations also include animations which are generated by rendering successive frames in the plot window. 
 
+The listed packages are grouped into general purpose and those designed for specific applications, such as maps and networks, or for particular plot types, such as parallel coordinate plots.
 
 # General purpose