The Google Charts API is quite powerful and via googleVis you can access it from R. Here is an example that demonstrates how you can zoom into your chart. In the example below I set the maximum zoom level to 5% of the chart. Drag and pan with a left mouse button to zoom in; use a right mouse click to zoom out again. The functionality is available in other core charts as well, such as line, column and bar charts. For more configuration options of the explorer settings visit the Google documentation. Loading R code
Last week I had the honour to give the opening keynote talk at the Talking Data South West conference, organised by the Exeter Initiative for Statistics and its Applications. The event was chaired by Steve Brooks and brought together over 100 people to discuss all aspects of data: from collection and analysis through to visualisation and communication.
Building interactive relationships with data and colleagues The programme was very good with a variety of talks such as How data collection from smart phones can improve agronomic decision making in potato crops by Robert Allen or Spatial data and analysis in the improvement of aquatic ecosystem health and drinking water quality by Nick Palling.
Today I feel very lucky, as I have been invited to the Royal Statistical Society conference to give a tutorial on interactive web graphs with R and googleVis. I prepared my slides with RStudio, knitr, pandoc and slidy, similar to my Cambridge R talk. You can access the RSS slides online here and you find the original R-Markdown file on github. You will notice some HTML code in the file, which I had to use to overcome my knowledge gaps of Markdown or its limitations.
Tonight I will give a talk at the Cambridge R user group about googleVis. Following my good experience with knitr and RStudio to create interactive reports, I thought that I should try to create the slides in the same way as well.
Christopher Gandrud’s recent post reminded me of deck.js, a JavaScript library for interactive html slides, which I have used in the past, but as Christopher experienced, it is currently not that straightforward to use with R and knitr.
Data analysis is often an iterative and interactive process. However, when I present about this subject, I feel often limited by the presentation software I use. It doesn’t matter if I use LaTeX/PDF, PowerPoint or Keynote. In all cases it is either very difficult or impossible to include interactive charts, such as Flash or SVG charts. As a result I have to switch between various applications during the talk. This can be fun, but quite often it is not.