Assignment 12b

library(tidyverse)
library(tidycensus)
library(sf)
library(scales)
library(viridis)
library(plotly)
library(RSocrata)
library(readr)
library(ggplot2)
library(knitr)

# Load and transform neighborhood data
raw_nabes <- st_read("~/Desktop/GRAD SCHOO/Year 1/Semester 1/Methods/part2/data/raw/geo/nynta2020_24c/nynta2020.shp") |>
  st_transform(crs = 4326)

# Filter cultural facilities related to "Libraries and Cultural Programs" and create sf object
cultural_facilities <- raw_facilities |>
  filter(FACDOMAIN == "LIBRARIES AND CULTURAL PROGRAMS", LATITUDE > 0, LONGITUDE != 0) |>
  st_as_sf(coords = c("LONGITUDE", "LATITUDE"), crs = 4326, remove = FALSE)

# Perform spatial join between cultural facilities and neighborhood boundaries
cultural_facilities_nabe <- st_join(cultural_facilities, raw_nabes, join = st_intersects)

# Select relevant columns
cultural_facilities_nabe <- cultural_facilities_nabe |>
  select(BORO, NTAName, OPNAME, FACTYPE, FACSUBGRP, FACGROUP, FACDOMAIN, OVERAGENCY, OVERABBREV, OVERLEVEL)

# Summarize the total number of cultural facilities by neighborhood
summary_cultural_facilities_nabe <- cultural_facilities_nabe |>
  group_by(NTAName, BORO) |>
  summarize(total_facilities = n(), .groups = "drop") |>
  arrange(desc(total_facilities))

# Summarize the total number of cultural facilities by borough
summary_cultural_facilities_boro <- summary_cultural_facilities_nabe |>
  st_drop_geometry() |>
  group_by(BORO) |>
  summarize(total_facilities = sum(total_facilities), .groups = "drop") |>
  arrange(desc(total_facilities))

kable(summary_cultural_facilities_boro, 
      col.names = c("Borough", "Total Facilities"), 
      caption = "Cultural Institutions by Borough in NYC", 
      format = "markdown")

Cultural Institutions by Borough in NYC

Borough	Total Facilities
MANHATTAN	1284
BROOKLYN	497
QUEENS	256
BRONX	107
STATEN ISLAND	67

# Spatially join summary back to the raw neighborhood boundaries
neighborhoods_with_facilities <- raw_nabes |>
  st_join(summary_cultural_facilities_nabe, join = st_intersects) |>
  mutate(total_facilities = replace_na(total_facilities, 0))

# Plot the map
ggplot(data = neighborhoods_with_facilities) +
  geom_sf(aes(fill = total_facilities), color = "white", size = 0.1) +  # Shade by facility count
  scale_fill_viridis_c(option = "plasma", name = "Cultural Facilities", direction = -1) +  # Use a nice color palette
  theme_minimal() +
  labs(
    title = "Number of Cultural Institutions per Neighborhood in NYC",
    subtitle = "Libraries and Cultural Programs",
    caption = "Source: NYC Open Data"
  ) +
  theme(
    legend.position = "bottom",
    axis.text = element_blank(),  # Remove axis text
    axis.ticks = element_blank(),  # Remove axis ticks
    panel.grid.major = element_blank(),  # Remove major gridlines
    panel.grid.minor = element_blank()   # Remove minor gridlines
  )