Global Mortality Rates

Global Mortality Rates

The following dataset is from the Tidy Tuesday https://github.com/rfordatascience/tidytuesday/tree/master/data/2018/2018-04-16.

library(tidyverse)
library(hrbrthemes) # custom dark theme from hrbrpackage

global_mort <- read_csv(file = "data/global_mortality.csv", col_names = TRUE) # import dataset into object

global_mort$country <- as.factor(global_mort$country) # Change character to factors

global_mort$country_code <- as.factor(global_mort$country_code)

global_mort$year <- as.factor(global_mort$year)

Graphical Display of mortality rates in Australia from 1990 to 2016

df <- global_mort %>% 
  group_by(country, year) %>% 
  pivot_longer(cols = c(4:35)) 

df$name <- factor(df$name)


df %>% 
  filter("Australia" %in% country) %>% 
  #filter("Alcohol disorders (%)" == name) %>% 
  #top_n(-15) %>% 
ggplot(aes(x = year, y = value, group = name)) +
 geom_line(aes(color = name), size = 1) +
 labs(x = "Year", y = "Percentage (%)", title = "Australian Mortality Rates", subtitle = "1990 to 2016") +
  theme_ft_rc() +
  theme(axis.text.x = element_text(size=10, angle=45)) +
  scale_y_percent()

# ggplotly(p)

df %>% 
  filter("Australia" %in% country) %>% 
  group_by(year, name) %>% 
  filter(name == "Alcohol disorders (%)")

## # A tibble: 27 x 5
## # Groups:   year, name [27]
##    country   country_code year  name                  value
##    <fct>     <fct>        <fct> <fct>                 <dbl>
##  1 Australia AUS          1990  Alcohol disorders (%) 0.216
##  2 Australia AUS          1991  Alcohol disorders (%) 0.215
##  3 Australia AUS          1992  Alcohol disorders (%) 0.213
##  4 Australia AUS          1993  Alcohol disorders (%) 0.216
##  5 Australia AUS          1994  Alcohol disorders (%) 0.218
##  6 Australia AUS          1995  Alcohol disorders (%) 0.225
##  7 Australia AUS          1996  Alcohol disorders (%) 0.225
##  8 Australia AUS          1997  Alcohol disorders (%) 0.232
##  9 Australia AUS          1998  Alcohol disorders (%) 0.234
## 10 Australia AUS          1999  Alcohol disorders (%) 0.244
## # ... with 17 more rows

Australia <- global_mort %>% 
  group_by(country, year) %>% 
  arrange(year) %>% 
  filter(country == "Australia")

ggplot(Australia) +
 aes(x = year, weight = `Cardiovascular diseases (%)`) +
 geom_bar(fill = ft_cols$blue) +
 labs(x = "", y = "Amount %", title = "Cardiovascular Disease in Australia", subtitle = "1990 to 2016") +
 theme_ft_rc()

# Drug Related Deaths in Australia
ggplot(Australia) +
  aes(x = year, weight = `Drug disorders (%)`) +
 geom_bar(fill = ft_cols$blue) +
 labs(x = "", y = "Amount %", title = "Drug Related Deaths in Australia", subtitle = "1990 to 2016") +
 theme_ft_rc()

ggplot(Australia) +
  aes(x = year, weight = `Suicide (%)`) +
 geom_bar(fill = ft_cols$blue) +
 labs(x = "", y = "Amount %", title = "Suicides in Australia", subtitle = "1990 to 2016") +
 theme_ft_rc()

ggplot(Australia) +
  aes(x = year, weight = `Alcohol disorders (%)` ) +
  geom_bar(fill = ft_cols$blue) +
 labs(x = "", y = "Amount %", title = "Alochol Use in Australia", subtitle = "1990 to 2016") +
 theme_ft_rc()