Nothing
knitr::opts_chunk$set(echo = FALSE, fig.width = 8) iname <- params$COIN$Data$Aggregated$UnitName[params$COIN$Data$Aggregated$UnitCode == params$usel] COIN <- params$COIN usel <- params$usel # generate big ranks and scores tables if not already present if(is.null(COIN$Results$FullRanks)){ COIN <- getResults(COIN, tab_type = "Full", use = "ranks", out2 = "COIN") } if(is.null(COIN$Results$FullScores)){ COIN <- getResults(COIN, tab_type = "Full", use = "scores", out2 = "COIN") } rnks <- COIN$Results$FullRanks scrs <- COIN$Results$FullScores
library(COINr) # plot bar chart iplotBar(COIN, dset = "Aggregated", isel = "Index", usel = usel, aglev = 4)
r iname
is ranked r rnks$Index[rnks$UnitCode == usel]
out of r nrow(rnks)
in the overall index. At the pillar level, its scores are summarised as follows:
# get summary table knitr::kable(getUnitSummary(COIN, usel = usel, aglevs = c(4,3,2)))
# plot bar chart iplotRadar(COIN, dset = "Aggregated", usel = usel, aglev = 2, addstat = "median")
At the indicator level, the main strengths of r iname
, as its top five highest ranking indicators, are as follows:
SAW <- getStrengthNWeak(COIN, usel = usel, withcodes = FALSE) knitr::kable(SAW$Strengths)
In terms of rankings, the weakest five indicators are the following:
knitr::kable(SAW$Weaknesses)
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