ukdemo <-
structure(list(region = structure(c(8L, 7L, 5L, 2L, 12L, 11L, 
4L, 3L, 1L, 6L, 10L, 9L), .Label = c("East Anglia", "East Midlands", 
"North East", "North West", "Northern Ireland", "Scotland", "South East (inc. London)", 
"South West", "UK Average", "Wales", "West Midlands", "Yorkshire & Humber"
), class = "factor"), debt = c(10737.65, 10501.219999999999, 
10091.959999999999, 9910.0400000000009, 9863.5200000000004, 9671.8199999999997, 
9287.0200000000004, 8729.6000000000004, 8609.4500000000007, 8398.7999999999993, 
8006.0600000000004, 9606.5200000000004), unemployment = c(3.2000000000000002, 
4.2999999999999998, 7.2999999999999998, 4.7999999999999998, 6, 
6.2000000000000002, 5.5, 7, 3.8999999999999999, 5.4000000000000004, 
5.2999999999999998, 4.9000000000000004), house = c(212572L, 306842L, 
144163L, 160323L, 150144L, 164716L, 147977L, 133460L, 228780L, 
163790L, 149807L, 189120L), pay = c(11.68, 14.880000000000001, 
10.5, 11.470000000000001, 11.5, 11.710000000000001, 11.92, 11.23, 
13.119999999999999, 12.279999999999999, 11.52, 12.57), rpi = c(99.5, 
102.3, 98.099999999999994, 99.400000000000006, 97, 100.59999999999999, 
98.200000000000003, 98.200000000000003, 101.2, 99.700000000000003, 
98.400000000000006, 100)), row.names = c(NA, -12L), class = c("tbl_df", 
"tbl", "data.frame"))