First steps in data visualisation using d3.js, by Mike Dewar This happens to be one of those rare instances where the benefit of hindsight does not make me regret something said flippantly on a panel. I deeply believe that in order to truly change the world we cannot simply "throw analytics at the problem." To that end, the medical and health industries are perhaps the most primed to be disrupted by data and analytics. To be successful, however, a deep respect for both the methodological and clinical contexts of the data are required.
D3.js animated map visualization - Mark Mark Oh Update: To create your own visualization like this, check out my project Datamaps. When you walk into Bazaarvoice’s office in Austin, TX, you can’t miss a giant screen in the main lobby displaying some interesting metrics regarding our business. Ordinal Scales · mbostock/d3 Wiki Wiki ▸ API Reference ▸ Scales ▸ Ordinal Scales Scales are functions that map from an input domain to an output range. Ordinal scales have a discrete domain, such as a set of names or categories.
Combining Plots R makes it easy to combine multiple plots into one overall graph, using either the par( ) or layout( ) function. With the par( ) function, you can include the option mfrow=c(nrows, ncols) to create a matrix of nrows x ncols plots that are filled in by row. mfcol=c(nrows, ncols) fills in the matrix by columns. # 4 figures arranged in 2 rows and 2 columns attach(mtcars) par(mfrow=c(2,2)) plot(wt,mpg, main="Scatterplot of wt vs. mpg") plot(wt,disp, main="Scatterplot of wt vs disp") hist(wt, main="Histogram of wt") boxplot(wt, main="Boxplot of wt") click to view