MTSU 2025 FMR

This is the fair market rent for the four closest ZIP codes to the MTSU campus

MTSU-area fair market rents, 2025
ZIP Studio BR1 BR2 BR3 BR4
37127 1410 1460 1620 2050 2520
37128 1680 1740 1930 2440 3000
37129 1630 1690 1870 2360 2910
37130 1300 1350 1490 1880 2320

Code:

# 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/fmr2025/fy2025_safmrs.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"
)

# 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("MTSU-area fair market rents, 2025") %>%
  cols_align(align = "left") %>%
  gt_theme_538
FMR_RuCo_table