Push the `knit` button!


```{r setup, child="exercise-setup.Rmd", eval = file.exists("exercise-setup.Rmd")}
```

```{r, include = FALSE}
knitr::opts_chunk$set(
  message = FALSE,
  error = FALSE,
  warning = FALSE
  )
```

```{r pkgs, message = FALSE, warning = FALSE}
library(tidyverse) # contains ggplot2, dplyr, tidyr, etc
library(ggthemes)
library(ggmap)
```

## `tuberculosis` dataset

```{r tb-data}
tb <- read_csv(here::here("data/TB_notifications_2020-07-01.csv")) %>% 
  dplyr::select(country, iso3, year, new_sp_m04:new_sp_fu) %>%
  pivot_longer(cols=new_sp_m04:new_sp_fu, names_to="sexage", values_to="count") %>%
  mutate(sexage = str_replace(sexage, "new_sp_", "")) %>%
  mutate(sex=substr(sexage, 1, 1), 
         age=substr(sexage, 2, length(sexage))) %>%
  dplyr::select(-sexage) %>%
  filter(!(age %in% c("04", "014", "514", "u"))) %>%
  filter(year > 1996, year < 2013) %>%
  mutate(age_group = factor(age, 
                            labels = c("15-24", "25-34", "35-44", 
                                       "45-54", "55-64", "65-"))) %>%
  dplyr::select(country, year, age_group, sex, count)

# Filter Australia
tb_oz <- tb %>% 
  filter(country == "Australia") 

# Fix names for map joining
tb_fixed <- tb %>% 
  mutate(region=recode(country, 
                       "United States of America"="USA", 
                       "United Kingdom of Great Britain and Northern Ireland"="UK",
                       "Russian Federation"="Russia",
                       "Viet Nam"="Vietnam",
                       "Venezuela (Bolivarian Republic of)"="Venezuela",
                       "Bolivia (Plurinational State of)"="Bolivia",
                       "Czechia"="Czech Republic",
                       "Iran (Islamic Republic of)"="Iran",
                       "Iran (Islamic Republic of)"="Laos",
                       "Democratic People's Republic of Korea"="North Korea",
                       "Republic of Korea"="South Korea",
                       "United Republic of Tanzania"="Tanzania",
                       "Congo"="Republic of Congo"))
tb_2012 <- tb_fixed %>% #<<
  filter(year == 2012) %>%
  group_by(region) %>%
  summarise(count = sum(count))
```

## `platypus` dataset

```{r platypus}
load(here::here("data/platypus.rda"))
oz_bbox <- c(112.9, # min long
              -45, # min lat
              159, # max long
              -10) # max lat
oz_map <- get_map(location = oz_bbox, source = "osm")
```

### Exercise 2.1: Polygon fill colour

```{r part2-exercise-02-01, echo = F, class = "target"}
knitr::include_graphics("images/part2-exercise-02/part2-exercise-01-1.png")
```

```{r part2-exercise-02-01s}
# add your code here!
```

### Exercise 2.2: Change the color palette

```{r part2-exercise-02-02, echo = F, class = "target"}
knitr::include_graphics("images/part2-exercise-02/part2-exercise-02-1.png")
```

```{r part2-exercise-02-02s}
# add your code here!
```

### Exercise 2.3:  Density plot on map

```{r part2-exercise-02-03, echo = F, class = "target"}
knitr::include_graphics("images/part2-exercise-02/part2-exercise-03-1.png")
```

```{r part2-exercise-02-03s}
# add your code here!
```

