Active Drilling Rigs Dashboard

Mr Cheerful
2 April 2017

John Hopkins University - Developing Data Products Course Project

“Energy Industry Indicators Brought to Life With Shiny”

Assignment

  • Create a Shiny application and deploy it on Rstudio's servers.
  • Use Slidify or Rstudio Presenter to prepare a reproducible pitch presentation about your application.

The Dashboard

  • The Active Drilling Rig Count

    • economic indicator for the upstream energy industry
    • widely regard as measure of economic status

  • Rig Count data is helpful in many decision making processes.

  • Rig Count Dashboard - graphical presentation of Rig Count.

    • enables the user to quickly examine the data
    • filter date range and regions to enhance understanding

Data

The data is obtained from the Baker Hughes Rig Count which is published weekly. The source data may be obtained in an Excel spreadsheet from the Baker Huges website. The Canadian data table was exported to a CSV file with the header shown below.

RigData <- read.csv("./CanadaActiveRigs/RigData.csv", header=TRUE, as.is=TRUE)
RigData$DATE <- as.Date(RigData$DATE)
head(RigData,3)[,1:8]

        DATE  AB BC Kavik MB NB NL.Land NL.OS
1 2003-03-28 195 69     0  0  0       0     4
2 2003-04-04 164 40     0  0  0       0     3
3 2003-04-11 139 22     0  0  0       0     3

Example Graph

The following plot shows the full dataset. In the application, filters can be used to restrict the time range and the regions shown to enhance it's readibility and usefulness.

RD <- melt(RigData, id.vars="DATE", variable_name="Region")
g <- ggplot(RD, aes(x=DATE, y=value)) + geom_line() + 
      ylab("Number of Active Rigs") ; print(g)

plot of chunk unnamed-chunk-2