radial_plot_dummy_data.R

df <- structure(list(Year = c("2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016", "2016"), 
Response = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L), 
.Label = c("Trustworthy", "Supportive", "Leading", "Strong", "Dependable", "Consultative", "Knowledgeable", "Sensible", "Intelligent", "Consistent", "Stable", "Innovative", "Aggressive", "Conservative", "Visionary", "Arrogant", "Professional", "Responsive", "Confident", "Accessible", "Timely", "Focused", "Niche", "None"), class = "factor"), Proportion = c(0.54, 0.48, 0.33, 0.35, 0.47, 0.3, 0.43, 0.29, 0.36, 0.38, 0.45, 0.32, 0.27, 0.22, 0.26, 0.95, 0.57, 0.42, 0.38, 0.5, 0.31, 0.31, 0.12, 0.88, 0.55, 0.55, 0.31, 0.4, 0.5, 0.34, 0.53, 0.3, 0.41, 0.41, 0.46, 0.34, 0.22, 0.17, 0.28, 0.94, 0.62, 0.46, 0.41, 0.53, 0.34, 0.36, 0.1, 0.84), 
n = c(240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L, 258L)),
.Names = c("Year", "Response", "Proportion", "n"), 
row.names = c(NA, -48L), 
class = c("tbl_df", 
"tbl", "data.frame"))