Biography

This is Zehao Xu, a PhD student of Statistics at the University of Waterloo, supervised by Wayne Oldford. My research interests include Data Visualization, Data Analysis, Interactive Graphics, Machine Learning, package Development.

Currently, I am dedicated to project loon, which is built by Prof.Oldford and Dr.Waddell

Welcome to Loon Wonderland

In package loon development, I am mainly in charge of building some new functions to better serve data scientists (e.g. loonGrob, facets, …) and fixing some tiny bugs.

Additionally, I am also interested in building some loon derivatives:

• loon.ggplot, an R package to turn ggplot graphic data structures into interactive loon plots.
• loon.shiny, display loon widgets in a shiny app
• loon.tourr provides tour mechanism (e.g. grand tour, guided tour, etc) in loon

Rasterly

Besides, I enjoy myself in large data visualization. So, a common question, how large is large? Is thousand large? Is million large? Is billion large? Trillion is large! In language R, most graphical systems can handle data points less than 10 thousand (with word handle, I mean the graphics can be rendered in reasonable time). Beyond it, the rendering time will increase dramatically (Don’t believe it? Try plot(rnorm(1e6))). If the number of observations reaches 1 million, R session may have a chance to be terminated. Package rasterly is built to visualize large data (even billion) in seconds.

Ggmulti

Everyone loves ggplot. It provides materials (i.e. serialaxes objects) to visualize high dimensional dataset in ggplot.

• Serialaxes coordinates (i.e., parallel or radial axis systems)

• General glyphs (e.g., polygons, images) to appear a scatterplot.

• “More general” geom_histogram and geom_density to allow them to appear on serial axes.