R/functions.R
CalculateGroupPath.RdConverts variable values into a set of radial x-y coordinates
CalculateGroupPath(df)Code adapted from a solution posted by Tony M to https://stackoverflow.com/questions/9614433/creating-radar-chart-a-k-a-star-plot-spider-plot-using-ggplot2-in-r.
a dataframe with Col 1 is group ('unique' cluster / group ID of entity) and Col 2-n are v1.value to vn.value - values (e.g. group/cluser mean or median) of variables v1 to v.n
a dataframe of the calculated axis paths
library(dplyr)
library(scales)
library(tibble)
mtcars_radar <- mtcars %>%
as_tibble(rownames = "group") %>%
mutate_at(vars(-group), rescale) %>%
tail(4) %>%
select(1:10)
plot.data <- as.data.frame(mtcars_radar)
if(!is.factor(plot.data[, 1])) {
plot.data[, 1] <- as.factor(as.character(plot.data[, 1]))
}
names(plot.data)[1] <- "group"
CalculateGroupPath(plot.data)
#> group x y
#> 1 Ferrari Dino 0.00000000 0.395744681
#> 2 Ferrari Dino 0.32139380 0.383022222
#> 3 Ferrari Dino 0.18153478 0.032009479
#> 4 Ferrari Dino 0.37639973 -0.217314488
#> 5 Ferrari Dino 0.13554715 -0.372412744
#> 6 Ferrari Dino -0.10992568 -0.302018314
#> 7 Ferrari Dino -0.10309826 -0.059523810
#> 8 Ferrari Dino 0.00000000 0.000000000
#> 9 Ferrari Dino -0.64278761 0.766044443
#> 10 Ferrari Dino 0.00000000 0.395744681
#> 11 Ford Pantera L 0.00000000 0.229787234
#> 12 Ford Pantera L 0.64278761 0.766044443
#> 13 Ford Pantera L 0.68757219 0.121237528
#> 14 Ford Pantera L 0.64875401 -0.374558304
#> 15 Ford Pantera L 0.23011494 -0.632235588
#> 16 Ford Pantera L -0.14490600 -0.398125971
#> 17 Ford Pantera L 0.00000000 0.000000000
#> 18 Ford Pantera L 0.00000000 0.000000000
#> 19 Ford Pantera L -0.64278761 0.766044443
#> 20 Ford Pantera L 0.00000000 0.229787234
#> 21 Maserati Bora 0.00000000 0.195744681
#> 22 Maserati Bora 0.64278761 0.766044443
#> 23 Maserati Bora 0.56474757 0.099580235
#> 24 Maserati Bora 0.86602540 -0.500000000
#> 25 Maserati Bora 0.12293812 -0.337769698
#> 26 Maserati Bora -0.17988633 -0.494233628
#> 27 Maserati Bora -0.01030983 -0.005952381
#> 28 Maserati Bora 0.00000000 0.000000000
#> 29 Maserati Bora -0.64278761 0.766044443
#> 30 Maserati Bora 0.00000000 0.195744681
#> 31 Volvo 142E 0.00000000 0.468085106
#> 32 Volvo 142E 0.00000000 0.000000000
#> 33 Volvo 142E 0.12257896 0.021613979
#> 34 Volvo 142E 0.17442914 -0.100706714
#> 35 Volvo 142E 0.21277751 -0.584601400
#> 36 Volvo 142E -0.11080018 -0.304421005
#> 37 Volvo 142E -0.42270288 -0.244047619
#> 38 Volvo 142E -0.98480775 0.173648178
#> 39 Volvo 142E -0.64278761 0.766044443
#> 40 Volvo 142E 0.00000000 0.468085106