In fergustaylor/openprescribingR: Load OpenPrescribing data directly into R

library(tidyverse)
library(openprescribingR)
library(sf)
library(gridExtra)
library(directlabels)

spendingdata <- spending_by_practice(BNF_section_code = "2.12", practice_code = "G82732")

ccgpracticespendingdata <- spending_by_practice(BNF_section_code = "2.12", CCG_code = "99J")

ccgpracticespendingdata2 <- spending_by_practice(BNF_section_code = "2.12", CCG_code = "99J") %>%
  group_by(date) %>% 
  summarise(`Q1`=quantile(actual_cost, probs=0.25),
            `Q2`=quantile(actual_cost, probs=0.5),
            `Q3`=quantile(actual_cost, probs=0.75),
            `Min`=min(actual_cost),
            `Max`=max(actual_cost),
            `Total`=sum(actual_cost)) %>%
  mutate(Clinic = spendingdata[, 'actual_cost'])
ccgpracticespendingdata2$date <- as.Date(ccgpracticespendingdata2$date)

tidyr <- ccgpracticespendingdata2 %>%
  gather(key = group, value = actual_cost, -date, -Total) %>%
  select(-Total)
tidyr$date <- as.Date(tidyr$date)

#add national average

spending_by_code(BNF_code = "2.12") %>%
  group_by(date)

spending_by_CCG(chemical_section_or_presentation_code = "2.12") %>%
  group_by(date) %>%
  summarise(`Average`= mean(actual_cost))

locations <- location_function(CCG_code = "99J", as_sf = TRUE) %>%
mutate(
    lon = map_dbl(geometry, ~st_centroid(.x)[[1]]),
    lat = map_dbl(geometry, ~st_centroid(.x)[[2]])
    )

ccgspendingdata <- spending_by_CCG(chemical_section_or_presentation_code = "2.12", CCG_code = "99J")

ccgpracticespendingdata$date <- as.Date(ccgpracticespendingdata$date)
plot1 = ccgpracticespendingdata %>%
  ggplot() +
  geom_step(aes(x= date, y=actual_cost, group=row_id)) +
  geom_step(data = filter(tidyr, group=="Clinic"|group=="Q2"),
            aes(x= date, y=actual_cost, group=group, colour=group), 
            size=2) + 
  geom_text(data = filter(ccgpracticespendingdata, date == "2017-05-01"), aes(label = row_id, x=date, y=actual_cost, 
    vjust = 1, hjust = 0, angle=45)) +
  theme(axis.text.x=element_text(angle=45, hjust = 1)) +
  labs(title="Actual_cost spending on 'BNF Section 2.12 Drugs - Lipid-Regulating Drugs'")
plot2 = ccgpracticespendingdata %>%
  ggplot() +
   geom_ribbon(data = ccgpracticespendingdata2, 
              aes(x = date, ymin = Min, ymax = Max), fill = "grey80", alpha=0.75) +
  geom_ribbon(data = ccgpracticespendingdata2, 
              aes(x = date, ymin = Q1, ymax = Q3), fill = "grey70", alpha=0.75) +
  geom_line(aes(group = row_id, x=date, y=actual_cost)) +
  geom_line(data = filter(tidyr, group=="Clinic"|group=="Q2"),
            aes(x= date, y=actual_cost, group=group, colour=group), 
            size=2) + 
  geom_text(data = filter(ccgpracticespendingdata, date == "2017-05-01"), aes(label = row_id, x=date, y=actual_cost, 
    vjust = 1, hjust = 0, angle=45)) +
  theme(axis.text.x=element_text(angle=45, hjust = 1)) +
  labs(title="Actual_cost spending on 'BNF Section 2.12 Drugs - Lipid-Regulating Drugs'")
grid.arrange(plot1, plot2)

plot3 <- tidyr %>%
ggplot(aes(x= date, y=actual_cost, group=group)) +
  geom_step() +
  geom_text(data = filter(tidyr, date == "2017-05-01"), 
            aes(label = group, x=date, y=actual_cost, vjust = 1, hjust = 0, angle=45)) +
  theme(axis.title.x=element_blank(),
        axis.text.x=element_blank(),
        axis.ticks=element_blank()) +
  labs(y = " ") +
  labs(title="Actual_cost spending on 'BNF Section 2.12 Drugs - Lipid-Regulating Drugs'")

plot4 <- tidyr %>%
ggplot() +
  geom_line(aes(x= date, y=actual_cost, group=group)) +
  geom_text(data = filter(tidyr, date == "2017-05-01"), aes(label = group, x=date, y=actual_cost, vjust = 1, hjust = 0, angle=45)) +
  theme(axis.title.x=element_blank(),
        axis.text.x=element_blank(),
        axis.ticks=element_blank())

plot5 <- tidyr %>%
  filter(group=="Clinic"|group=="Q2") %>%
ggplot() +
  geom_ribbon(data = ccgpracticespendingdata2, 
              aes(x = date, ymin = Min, ymax = Max), fill = "grey80", alpha=0.75) +
  geom_ribbon(data = ccgpracticespendingdata2, 
              aes(x = date, ymin = Q1, ymax = Q3), fill = "grey70", alpha=0.75) +
  geom_line(aes(x= date, y=actual_cost, group=group, colour=group), size=2) +
  geom_text(data = filter(tidyr, date == "2017-05-01"), 
            aes(label = group, x=date, y=actual_cost, vjust = 1, hjust = 0, angle=45)) +
  theme(axis.text.x=element_text(angle=45, hjust = 1)) +
  theme(legend.position="none") +
  labs(y = " ")

grid.arrange(plot3, plot4, plot5)