---

title: “FMR data with Rental homes” author: “Jhawk” date: “2025-03-03” output: html_document

Below is the FMR 2025 map with Rental homes included in the data

# Installing and loading required packages

if (!require("tidyverse"))
  install.packages("tidyverse")
if (!require("gtExtras"))
  install.packages("gtExtras")
if (!require("leafpop"))
  install.packages("leafpop")
if (!require("sf"))
  install.packages("sf")
if (!require("mapview"))
  install.packages("mapview")
if (!require("RColorBrewer"))
  install.packages("RColorBrewer")
if (!require("tidycensus"))
  install.packages("tidycensus")

library(tidyverse)
library(gtExtras)
library(sf)
library(mapview)
library(leafpop)
library(RColorBrewer)
library(tidycensus)

# Transmitting API key

census_api_key("494018a70f114d4f76b10537730ccc9c7dbfe36b")

# Fetching the Census data

Census_Data <- get_acs(
  geography = "zcta",
  variables = c("DP04_0047", "DP04_0045"),
  year = 2023,
  survey = "acs5",
  output = "wide",
  geometry = FALSE
)

# Making better column names

Census_Data <- Census_Data %>% 
  rename(c("Rentals" = "DP04_0047E",
           "Rentals_MOE" = "DP04_0047M",
           "Households" = "DP04_0045E",
           "Households_MOE" = "DP04_0045M"))

# A peek at the data

glimpse(Census_Data)
# Redownloading the rent data

FMR_RuCo <- read_csv("https://raw.githubusercontent.com/drkblake/Data/refs/heads/main/FMR_RuCo.csv")

# Redownloading, unzipping and importing the ZIP code map file

download.file(
  "https://www2.census.gov/geo/tiger/GENZ2020/shp/cb_2020_us_zcta520_500k.zip",
  "ZCTAs2020.zip"
)

unzip("ZCTAs2020.zip")

ZCTAMap <- read_sf("cb_2020_us_zcta520_500k.shp")

# Merging the rent data and ZIP code map

FMR_RuCo$ZIP <- as.character(FMR_RuCo$ZIP)

FMR_RuCo_Map <- left_join(FMR_RuCo, ZCTAMap, by = c("ZIP" = "ZCTA5CE20"))

FMR_RuCo_Map <- FMR_RuCo_Map %>%
  select(-c(AFFGEOID20, GEOID20, NAME20, LSAD20, ALAND20, AWATER20))

FMR_RuCo_Map <- st_as_sf(FMR_RuCo_Map)

# Mapping by average rent with "Blues" color scheme

ZIP_Map <- mapview(
  FMR_RuCo_Map,
  zcol = "ZIP_Average",
  col.regions = brewer.pal(9, "Oranges"),
  layer.name = "Average rent",
  popup = popupTable(
    FMR_RuCo_Map,
    feature.id = FALSE,
    row.numbers = FALSE,
    zcol = c("ZIP", "Studio", "BR1", "BR2", "BR3", "BR4")
  )
)

# Showing the map

ZIP_Map
# Merging FMR_RuCo_Map and Census_Data

FMR_RuCo_Map <- left_join(FMR_RuCo_Map, Census_Data, by = c("ZIP" = "GEOID"))
# Mapping by ZIP code

ZIP_Map <- mapview(
  FMR_RuCo_Map,
  zcol = "ZIP_Average",
  col.regions = brewer.pal(9, "Oranges"),
  layer.name = "Average rent",
  popup = popupTable(
    FMR_RuCo_Map,
    feature.id = FALSE,
    row.numbers = FALSE,
    zcol = c("ZIP", "Studio", "BR1", "BR2", "BR3", "BR4",
             "Rentals", "Rentals_MOE", "Households", "Households_MOE")
  )
)

# Showing the map

ZIP_Map
# ACS codebooks

DetailedTables <- load_variables(2023, "acs5", cache = TRUE)
ProfileTables <- load_variables(2023, "acs5/profile", cache = TRUE)
SubjectTables <- load_variables(2023, "acs5/subject", cache = TRUE)