data-raw/aggregate_data/proximity_measures/04-aggregate.R

In purposeanalytics/lemur: Low-end of Market Rental Monitor

# Amenity density only - by neighbourhood
# Aggregate and add to city_profiles and neighbourhood_profiles for easier visualizing

library(dplyr)
library(lemr)
library(tidyr)
library(purrr)
library(forcats)
library(sf)

proximity_measures <- readRDS(here::here("data-raw", "aggregate_data", "proximity_measures", "final", "proximity_measures.rds"))

amenity_density <- proximity_measures %>%
  as_tibble() %>%
  distinct(dbuid, population, amenity_dense, neighbourhood) %>%
  mutate(
    amenity_dense = fct_relevel(amenity_dense, "High", "Medium", "Low", "Unknown"),
    amenity_dense = fct_rev(amenity_dense)
  ) %>%
  arrange(amenity_dense)

# Aggregate by neighbourhood
amenity_density_by_neighbourhood <- amenity_density %>%
  group_by(neighbourhood, group = amenity_dense) %>%
  summarise(population = sum(population), .groups = "drop_last") %>%
  mutate(prop = round(population / sum(population), 3)) %>%
  ungroup() %>%
  complete(neighbourhood, group, fill = list(prop = 0)) %>%
  select(neighbourhood, group, prop) %>%
  arrange(neighbourhood) %>%
  split(.$neighbourhood)

# Aggregate by city
amenity_density_city <- amenity_density %>%
  group_by(group = amenity_dense) %>%
  summarise(population = sum(population), .groups = "drop_last") %>%
  mutate(prop = round(population / sum(population), 3)) %>%
  select(group, prop)

saveRDS(amenity_density_by_neighbourhood, here::here("data-raw", "aggregate_data", "proximity_measures", "aggregate", "amenity_density_by_neighbourhood.rds"))
saveRDS(amenity_density_city, here::here("data-raw", "aggregate_data", "proximity_measures", "aggregate", "amenity_density_city.rds"))