The vignettes (https://mran.microsoft.com/web/packages/fivethirtyeight/vign...) are a good tutorial in dplyr/ggplot2 too.
https://www.r-bloggers.com/interactive-visualizations-with-r...
None of them are as flexible as D3, but there are packages to output from R to D3 out there.
Here's a higher-level demo of ggplotly in one of my R Notebooks: http://minimaxir.com/notebooks/breach-network/
Shiny requires an external server and is often overkill for static data.
(You can build a Plotly chart in ggplot, embed it in a web page and then script it with JS to get a visualization. Frankly, that's a PITA. You can write R/shiny code that will generate a visualization, with HTML controls etc, and you end up writing a web app in R and that's a different PITA. I would like to see Plotly generate a web wrapper that automates wiring up a plotly graph and scripting it from an app so you can update data on the fly to make it a visualization. Supposedly they are working on it with their dash framework, but it's not released yet.)
The embed-directly-into-HTML is the approach I use for my Jekyll blog and it does not require much effort. (I just have to set a YAML flag to load Plotly library)
The part that requires some custom Plotly coding is when you want to script the chart ... have HTML buttons, sliders, to filter, recompute, revisualize the data.
It's beautiful that it even works, and you can programmatically update the JSON of an embedded chart. But it would be nice if you could give Plotly a dataset, plot the data, and say, give me a button to filter rows using these criteria for this column (or run some other code on the data) and re-render the chart. Right now you have to code that manually and update the JSON model.
Visualization used to mean charts that were animated and/or would dynamically update but now it means any old chart LOL.