In CaRdiffR/tdor: Data for the Transgender Day of Remembrance

[TRIGGER WARNING: VIOLENCE. MURDER]

The data can be explored through this website: [https://tdor.translivesmatter.info/]

knitr::opts_chunk$set(echo = TRUE)

Load required packages.

library(dplyr)
library(ggplot2)
library(ggthemes)
library(lubridate)
library(maps)
library(tdor)

Some code and graphs to explore the 2019 data

The TDoR 2019 period goes from 1st of Oct 2018 to 30th of Sep 2019. The relevant records can be obtained using the TDoR variable.

How many deaths have occured in this time?

year <- 2019
start <- make_date(year, 10, 1)
end <- make_date(year, 9, 30)
tdor %>% 
  filter(TDoR == year) -> tdor_subset

There were r nrow(tdor_subset) deaths reported between r start and r end.

tdor_subset %>% 
  mutate(yrmth = make_date(Year, Month, 1)) %>% 
  ggplot(aes(yrmth)) + geom_bar() +
    labs(title = "Deaths by month", x = "",
      subtitle = paste("between", start, "and", end),
      y = "Deaths") +
    theme_bw()

Where we have ages... what were those ages?

tdor_subset %>%
  ggplot(aes(x = (`Age min` + `Age max`)/2)) + 
  geom_bar() +
  ggtitle("Deaths by age") +
  labs(y = "Deaths", x = "Age at death",
      subtitle = paste("between", start, "and", end)) +
  theme_bw()

Show top 10 countries for reported deaths

tdor_subset %>%
  group_by(Country) %>%
  summarise(n = n()) %>%
  arrange(desc(n)) -> by_country

ggplot(by_country[1:10,],
  aes(x = Country,
      y = n)) +
  theme_bw() +
  labs(y = "Deaths", x = "") +
  geom_bar(stat="identity") +
  theme(axis.text.x = element_text(angle=45, hjust=1)) +
  labs(title = "Ten countries with the most reported deaths",
    subtitle = paste("betweeen", start, "and", end))

world <- ggplot() +
  borders("world", colour = "gray85", fill = "gray80") +
  theme_map() 

map <- world +
  geom_point(aes(x = Longitude, y = Latitude),
             data = tdor_subset, 
             colour = 'purple', alpha = .2) +
  ggtitle(paste("Map of deaths betweeen", start, "and", end))

map