library(cqcr)
library(purrr)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(ggplot2)
library(forcats)

loc1 <- cqc_locations_search(care_home = TRUE, 
                             local_authority = c("Waltham Forest",
                                                 "Hackney", "Tower Hamlets"))


care_home_details <- cqc_location_details(loc1)

care_home_df <- map_dfr(care_home_details, `[`,
                        c("location_id", "name", "number_of_beds", 
                          "onspd_longitude", "onspd_latitude"))

care_home_df <- care_home_df %>% 
  mutate(rating = care_home_details %>%
           map(c("current_ratings", "overall", "rating")) %>%
           as.character(),
         rating = recode(rating, "NULL" = "No published rating"),
         rating = factor(rating, levels = c("Outstanding", "Good",
                                            "Requires improvement", 
                                            "Inadequate",
                                            "No published rating")),
         report_date = care_home_details %>%
           map(c("current_ratings", "reportDate")) %>%
           as.character(),
         report_date = ifelse(report_date == "NULL", NA, report_date),
         specialisms = care_home_details %>% map(c("specialisms", "name")))

care_home_df_unnest <- tidyr::unnest(care_home_df, cols = c(specialisms)) %>%
  mutate(specialisms = fct_infreq(specialisms))

theme_set(theme_bw())

ggplot(care_home_df_unnest,
                        aes(x = specialisms, fill = rating)) + 
  geom_bar() + 
  scale_x_discrete(labels = scales::wrap_format(33)) + 
  scale_fill_viridis_d(name="", option = "A", end = 0.95) + 
  labs(x = "Specialism(s)", y = "Number of Care Homes") + 
  theme(legend.position = "bottom",
        axis.text.x = element_text(size = 8, angle = 60, hjust = 1))