Time Series analysis is a fundamental aspect of performance management. Before we can begin to model time-series there’s huge dividend in just visualising the data. We can see if there is a seasonal pattern, or is the time-series additive or multiplicative.

R comes with good plotting but one thing I’ve always wanted to do is zoom around a time-series. This is because patterns at the lower level are not always visible. We often have to group time to see the pattern but this is a transform I could do without.

At the last R London meetup I saw an excellent presentation from Enzo Martoglio who demonstrated HTML Widgets. HTML widgets for R provide a bridge between R and HTML/JavaScript visualization libraries.

This opens a door for analysts and enables modern tools to be used for communicating model output. I’ll leave that for another post. Back to time-series.

I kid you not, with 3 lines of code I was able to create an interactive time-series chart with zoom. The package to use is dygraphs. Basic example below.

#Data sourced from Rob Hyndman's Time Series Data Library 
#Hyndman, R.J. Time Series Data Library, http://data.is/TSDLdemo 
#Data Description 
#Monthly sales for a souvenir shop on the wharf at a beach resort town 
#in Queensland, Australia. Jan 1987-Dec 1993 

library(dygraphs) 
library(fma) 
dygraph(fancy,main = "Monthly Sales") %>% dyRangeSelector() 

We can see the seasonal pattern and the multiplicative trend. This means a log transform will be needed before an additive model can be used. I’ll be posting more about time-series in the coming months.

These widgets can be output to the usual places:

• R Console
• R Markdown document
• Shiny Web App

There are so many use cases for this. It’s going to be interesting to see where things go.