Here are fair market rents for various apartment sizes in Rutherford County ZIP codes.
Rutherford FMR, by size and ZIP | |||||
ZIP | Studio | BR1 | BR2 | BR3 | BR4 |
---|---|---|---|---|---|
37037 | 1660 | 1710 | 1920 | 2410 | 2940 |
37085 | 1260 | 1290 | 1450 | 1820 | 2210 |
37086 | 1580 | 1620 | 1820 | 2290 | 2790 |
37118 | 1100 | 1130 | 1270 | 1590 | 1960 |
37127 | 1240 | 1270 | 1430 | 1800 | 2190 |
37128 | 1510 | 1550 | 1740 | 2190 | 2670 |
37129 | 1420 | 1460 | 1640 | 2060 | 2510 |
37130 | 1180 | 1210 | 1360 | 1710 | 2080 |
37132 | 1180 | 1210 | 1360 | 1710 | 2080 |
37149 | 1100 | 1130 | 1270 | 1590 | 1960 |
37153 | 1410 | 1450 | 1630 | 2040 | 2490 |
37167 | 1290 | 1330 | 1490 | 1870 | 2280 |
# Installing and loading required packages
if (!require("tidyverse"))
install.packages("tidyverse")
if (!require("gtExtras"))
install.packages("gtExtras")
library(tidyverse)
library(gtExtras)
library(readxl)
# Downloading data from:
# https://www.huduser.gov/portal/datasets/fmr/smallarea/index.html#year2024
download.file("https://www.huduser.gov/portal/datasets/fmr/fmr2024/fy2024_safmrs_revised.xlsx", "rent.xlsx", mode = "wb")
# Reading the downloaded Excel file into a data frame called FMR
FMR <- read_xlsx(path = "rent.xlsx", .name_repair = "universal")
# Making a list of Rutherford County ZIP codes
ZIPList <- c(
"37127",
"37128",
"37129",
"37130",
"37132",
"37085",
"37118",
"37149",
"37037",
"37153",
"37167",
"37086"
)
# Filtering for Rutherford ZIP codes and
# selecting columns of interest
FMR_RuCo <- FMR %>%
filter(ZIP.Code %in% ZIPList) %>%
select(ZIP.Code,
SAFMR.0BR,
SAFMR.1BR,
SAFMR.2BR,
SAFMR.3BR,
SAFMR.4BR) %>%
distinct()
# Renaming the columns
colnames(FMR_RuCo) <- c("ZIP",
"Studio",
"BR1",
"BR2",
"BR3",
"BR4")
# Showing the data as a table
FMR_RuCo_table <- gt(FMR_RuCo) %>%
tab_header("Rutherford FMR, by size and ZIP") %>%
cols_align(align = "left") %>%
gt_theme_538
FMR_RuCo_table