In fergustaylor/openprescribingR: Load OpenPrescribing data directly into R

library(tidyverse)
library(openprescribingR)
library(sf)
library(ggplot2)
library(gridExtra)
library(ggrepel)
library(ggiraph)

ccggeom <- CCG_boundaries_or_location(as_sf = TRUE) %>%
  dplyr::rename(row_name = name) %>%
  select(-ons_code, -org_type)

dataframe <- dplyr::full_join(

  (openprescribingR::list_size() %>%
  select(-row_id)), 

  (spending_by_CCG(chemical_section_or_presentation_code = "7.4.5")), 

  by = c("row_name", "date")) %>%
  dplyr::mutate(costperperson = actual_cost/total_list_size) %>%
  dplyr::full_join(ccggeom, by="row_name") %>%
  st_as_sf() %>%
  dplyr::mutate(label = stringr::str_c(row_name, " £", format(round(costperperson, 2), nsmall = 2))) %>%
  dplyr::mutate(label2 = stringr::str_c("£", format(round(costperperson, 2), nsmall = 2)))

rm(ccggeom)

#Find empty geometries
#st_dimension(st_sfc(dataframe$geometry))

#Dataframe without empty geoms
dataframe <- dataframe[c(!is.na(st_dimension(st_sfc(dataframe$geometry)))),]

#Centroids
dataframe <- dataframe %>%
  mutate('lon' = st_coordinates(st_centroid(dataframe$geometry))[,1]) %>%
  mutate('lat' = st_coordinates(st_centroid(dataframe$geometry))[,2])

plot1 <- filter(dataframe, date == "2017-05-01") %>%
  ggplot() +
  geom_sf()

plot2 <- filter(dataframe, date == "2017-05-01") %>%
  ggplot() +
  geom_sf(aes(fill = costperperson)) +
  theme(legend.position="none")

ggsave("openprescribingRplots/plot1.png", plot = plot1)
ggsave("openprescribingRplots/plot2.png", plot = plot2)

selectiondata <- filter(dataframe, date == "2017-05-01")
polygons <- fortify(as_Spatial(selectiondata$geometry))

#adding costperperson/name to polygons
selectiondata$id <- str_c("ID", 1:207)

for (i in 1:length(selectiondata$costperperson)){
polygons$label2[!is.na(match(polygons$id, selectiondata$id[i]))] <- as.character(selectiondata$label2[i])
polygons$costperperson[!is.na(match(polygons$id, selectiondata$id[i]))] <- as.character(selectiondata$costperperson[i])
polygons$label[!is.na(match(polygons$id, selectiondata$id[i]))] <- as.character(selectiondata$label[i])
polygons$name[!is.na(match(polygons$id, selectiondata$id[i]))] <- as.character(selectiondata$row_name[i])
}

plot3 =  ggplot() +
  geom_polygon_interactive(data = polygons, aes(x = long, y = lat, group = group, tooltip = name)) +
  coord_sf(crs= 4326, datum = sf::st_crs(4326))
ggiraph(code = {print(plot3)}, width_svg = 17.07, height_svg = 13.46, width=1) %>%
htmlwidgets::saveWidget("plot3.html")

plot4 =  ggplot() +
  geom_sf(data = selectiondata, aes(fill = costperperson)) +
  geom_polygon_interactive(data = polygons, aes(x = long, y = lat, group = group, tooltip = label2), alpha = 0.1) +
  scale_fill_continuous(breaks = c(0.04, 0.06, 0.08, 0.10, 0.12),
  labels = c("£0.04", "£0.06", "£0.08", "£0.10", "£0.12")) +
  coord_sf(crs= 4326, datum = sf::st_crs(4326))
ggiraph(code = {print(plot4)}, width_svg = 17.07, height_svg = 13.46, width=1)  %>%
htmlwidgets::saveWidget("plot4.html")

plot5 =  ggplot() +
  geom_sf(data = selectiondata, aes(fill = costperperson)) +
  geom_polygon_interactive(data = polygons, aes(x = long, y = lat, group = group, tooltip = label, data_id = id), alpha = 0.1) +
  coord_sf(crs= 4326, datum = sf::st_crs(4326)) +
  scale_fill_continuous(breaks = c(0.04, 0.06, 0.08, 0.10, 0.12),
  labels = c("£0.04", "£0.06", "£0.08", "£0.10", "£0.12")) +
  labs(title="Actual_cost/total_list_size spending on 'BNF Section 7.4.5 Drugs', May 2017")

ggiraph(code = {print(plot5)}, hover_css = "stroke: white;", width_svg = 17.07, height_svg = 13.46, width=1) %>%
htmlwidgets::saveWidget("plot5.html")

gif <- ggplot(dataframe %>% dplyr::filter(dataframe$date == "2017-01-01" | dataframe$date == "2017-02-01" | dataframe$date == "2017-03-01" | dataframe$date == "2017-04-01" |dataframe$date == "2017-05-01")) +
  geom_sf(aes(fill = costperperson, frame=date)) +
  theme(legend.position="none")

gganimate::gganimate(gif, "openprescribingRplots/output.gif")