Chapter 15 Victim Descent

We examine the Descent of the Victims in the barplot.

VictimDescentAbbr = c("A","B","C","D","F","G","H","I","J","K","L","O","P","S","U","V","W","X","Z")
VictimDescentDescription = c("Other Asian","Black",
                             "Chinese","Cambodian","Filipino",
                             "Guamanian","Hispanic/Latin/Mexican",
                             "American Indian/Alaskan Native",
                             "Japanese","Korean","Laotian ",
                             "Other","Pacific Islander",
                             "Samoan","Hawaiian","Vietnamese",
                             "White","Unknown","AsianIndian")

VictimDescentFull = data.frame(VictimDescent = as.character(VictimDescentAbbr),
                               VictimDescentDescription = as.character(VictimDescentDescription))

LACrime$VictimDescent = as.character(LACrime$VictimDescent)

LACrime %>%
  filter(!is.na(VictimDescent)) %>%
  group_by(VictimDescent) %>%
  tally() %>%
  ungroup() %>%
  arrange(desc(n)) %>%
  inner_join(VictimDescentFull) %>%
  head(10) %>%
  mutate(VictimDescentDescription = reorder(VictimDescentDescription,n)) %>%
  
  ggplot(aes(x = VictimDescentDescription,y = n)) +
 geom_bar(stat='identity',colour="white", fill =fillColor2) +
 geom_text(aes(x = VictimDescentDescription, y = 1, label = paste0("(",n,")",sep="")),
           hjust=0, vjust=.5, size = 4, colour = 'black',
           fontface = 'bold') +
 labs(x = 'VictimDescent', y = 'Count of Incidents', 
      title = 'Count of Incidents and VictimDescent') +
 coord_flip() + 
 theme_bw()

We observe Hispanic, White and Black are the top categories where the Victims are present.