week-45.Rmd

---
title: "week-45"
author: "Maxwel Coura Oliveira"
date: "11/2/2021"
output: html_document
---

```{r}
# Get the Data

library(spData)

# note that spDataLarge needs to be installed via:
# install.packages("spDataLarge", 
# repos = "https://nowosad.github.io/drat/", type = "source")
library(spDataLarge)
library(sf)
library(raster)
library(tidyverse)
library(rvest)
```

```{r}
country_function <- function(id) {
  
  url <- paste0("http://weedscience.org/Summary/Country.aspx?CountryID=",id,"")
  #id will change by each country id number
  
  # Read url
  resistance <- read_html(url)
  
  # Extract herbicide resistance data
  chart <- resistance %>% 
    html_node(".rgMasterTable") %>% # selector
    html_table(fill = TRUE) # get the table

  # Tidy dataset
  final_chart <- chart %>% 
    janitor::row_to_names(row_number = 2) %>% # make second column header
    janitor::clean_names() %>% # clean header
    as_tibble() %>% # tibble is better than data.frame
    drop_na() %>% # drop NA values
    mutate_at(c("number", "first_year", 
                "country_id", "resist_id"), 
              as.integer) # make columns numbers as integer 
  # Get final dataset
  final_chart 
}
```

```{r}
country_function(id = 45) |> # usa id
  count(state_name) |> 
  rename(n_cases = n) -> n_cases
```

```{r}
country_function(id = 45) |> # usa id
  count(state_name, common_name) |> 
  count(state_name) |> 
  rename(n_species = n) -> species_n
```

```{r}
country_function(id = 45) |> # usa id
  count(state_name, site_of_action) |> 
  count(state_name) |> 
  rename(n_soa = n) -> soa_n
```

```{r}
library(geofacet)
library(ggtext)
library(biscale)
library(cowplot) 
```


```{r}
n_cases |> 
  left_join(species_n, by = "state_name") |> 
  left_join(soa_n, by = "state_name") |> 
  add_row(state_name = "Puerto Rico", n_cases = 0, n_species = 0, n_soa = 0) |> 
  add_row(state_name = "Alaska", n_cases = 0, n_species = 0, n_soa = 0) |> 
  add_row(state_name = "Nevada", n_cases = 0, n_species = 0, n_soa = 0) |> 
  bi_class(x = n_cases, y = n_species, style = "quantile", dim = 3) -> dataset
```


```{r}
us_state_grid1 %>% 
  add_row(row = 7, col = 10, code = "PR", name = "Puerto Rico") -> us_state_grid1_2
```



```{r}
dataset |> 
  left_join(us_state_grid1_2, 
            by = c("state_name" = "name")) |> 
  mutate(ratio = round(n_cases / n_species, 2)) -> dataset1
```



```{r}
# Palette
custom_pal <- bi_pal_manual(val_3_1 = "#F46D43", val_3_2 = "#D73027", val_3_3 = "#A50026",
                            val_2_1 = "#D9EF8B", val_2_2 = "#FFFFBF",val_2_3 = "#FEE08B",
                            val_1_1 = "#006837", val_1_2 = "#1A9850",val_1_3 = "#66BD63")


(legend <- bi_legend(pal = custom_pal,
                    dim = 3,
                    xlab = "Higher number of cases",
                    ylab = "Higher number of species",
                    size = 8) + 
  bi_theme() + 
  theme(
        rect = element_rect(fill = "grey10"),
        panel.border = element_blank(),
        axis.ticks = element_blank(),
        axis.text = element_blank(),
        axis.title.x = element_text(size = 9,
                                    color = "#F46D43", 
                                    face = "bold"),
        axis.title.y = element_text(size = 9,
                                    color = "#66BD63",
                                    face = "bold"),
        plot.background = element_rect(fill = "#F9F6EE", 
                                       color = NA),
        panel.background = element_rect(fill = "#F9F6EE", 
                                        color = NA))
)
```

```{r}
dataset1 %>% 
  ggplot() + 
  geom_rect(aes(fill = bi_class), xmin = -1, ymin = -1, xmax = 1, ymax = 1, 
            color = "white") +
  geom_richtext(aes(label = code, 
                color = ifelse(str_detect(bi_class,"1-1|1-2|3-3"), "white", "#333333")),
                hjust = 0.5,
                size = 10,
                x = 0, y = 0,
                fontface = "bold",
                fill = NA, 
                label.colour = NA, 
                show.legend = F) +
  facet_geo(vars(state_name), grid = us_state_grid1_2) +
  coord_fixed(xlim =c(-1,1), 
              ylim = c(-1,1)) +
  scale_color_identity() +
  bi_scale_fill(pal = custom_pal, 
                dim = 3 , 
                guide = "none") +
  theme_minimal() +
  labs(
    title = "Herbicide Weed Resistance in the US",
    subtitle = "A bivariate map showing reported resistance cases vs resistant weed species",
    caption = "**Source:** WeedScience.org | **Figure:** @maxwelco"
  ) +
  theme(
    panel.spacing = unit(-5,"points"),
    strip.text = element_blank(),
    plot.title = element_text(size = 30, 
                              color = "#333333",
                              hjust = .5, margin = margin(t = 10, b = 15),  
                              face = "bold"),
    plot.subtitle = element_text(size = 15, hjust = 0.5),
    plot.caption = element_markdown(size = 10, 
                                    hjust = 1, 
                                    color = "#333333"),
#    plot.margin = margin(t = 20, r = 10, b =10, l = 10), 
    plot.background = element_rect(fill = "#F9F6EE", color = NA)
  ) -> map 

ggdraw() +
  draw_plot(map, 0, 0, 1, 1) +
  draw_plot(legend, 0.1, 0.8, 0.2, 0.2)

ggsave("fig_45.png", width = 16, height = 9)
```