Interactive statistical graphics toolkits play an important role in the exploratory phase of a data analysis cycle. Web graphics are rarely used during this phase, and are commonly reserved solely for the presentation of findings, mainly due to a lack of tools for quick iteration. The R package ggplot2 is a popular tool for data visualization with an elegant framework allowing useRs to quickly iterate through many plots with a minimal amount of friction. The R package plotly converts ggplot2 graphics to a web-based version, adding automatic support for interactivity such as pan, zoom, and identification (i.e., tooltips). It also has support for more advanced interactive techniques, such as linked brushing, thanks to infrastructure provided by the R packages shiny and htmlwidgets. In this talk, I'll present numerous examples that demonstrate these techniques, and how to they can used to derive insights from data.