Question 1

How do I customize hover tooltips in plotly for R?

Accepted Answer

Use the text aesthetic in ggplot2 or the style() function on a ggplotly object to modify hoverinfo and hoverlabel. For example, add text = ~variable in ggplot2, then use style(gg, hoverinfo = 'x+y+text') for precise control.

Question 2

Is plotly for R better than ggiraph for interactive plots?

Accepted Answer

Plotly for R offers more chart types and deeper interactivity via plotly.js, while ggiraph is lighter and more ggplot2-centric. Choose plotly for complex dashboards and web deployment, but ggiraph for simpler, tooltip-focused enhancements.

Question 3

Can I use plotly in Shiny without knowing JavaScript?

Accepted Answer

Yes, plotly for R provides native Shiny integration with renderPlotly() and plotlyOutput(), allowing full interactivity through R code alone. The package handles JavaScript rendering automatically in the background.

Question 4

How to save plotly interactive plots as static images?

Accepted Answer

Use the plotly::export() function or the orca command-line tool for high-quality static exports. Alternatively, capture the HTML with webshot2, but this requires additional setup and dependencies.

Question 5

What doesn't ggplotly() convert well from ggplot2?

Accepted Answer

Complex layered geoms, custom stat transformations, or non-standard themes may not translate perfectly. You might need to use add_traces() or adjust layout() manually to replicate advanced ggplot2 features in the interactive version.

Question 6

Is plotly for R good for big data visualization?

Accepted Answer

It depends on dataset size and browser capabilities. Plotly.js can handle moderate datasets, but for massive data, consider server-side aggregation or alternative R packages like plotly with partial updates, as client-side rendering may slow down.

plotly

What is plotly?

Overview

Use Cases

Best For

Related Projects

Found a gem we're missing?

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions