In Rutherford County, the gap between studio and four-bedroom rents depends heavily on where you live.
The size of the price gap between studio and four-bedroom rents, likely reflects the various kinds of four-bedroom housing found across Rutherford County. In some ZIP codes, four-bedroom rentals are often newer single-family homes or upscale apartment units, marketed with amenities and in proximity to shopping and dining. In other parts of the county, four-bedroom units cater to student-oriented housing, where individual bedrooms are rented separately within a shared living space.
The table below displays rents across selected ZIP codes in Rutherford County, using HUD’s 2026 Small Area Fair Market Rents. ZIP codes are ordered from the largest to the smallest rent gap, highlighting where housing costs rise most sharply with unit size and offering a snapshot of how rental affordability varies across the county:
| Rutherford Rent Analysis | ||||||
| ZIP | Studio | BR1 | BR2 | BR3 | BR4 | Spread |
|---|---|---|---|---|---|---|
| 37037 | 1900 | 1990 | 2180 | 2790 | 3400 | 1500 |
| 37086 | 1730 | 1820 | 1990 | 2540 | 3100 | 1370 |
| 37153 | 1670 | 1750 | 1920 | 2450 | 2990 | 1320 |
| 37128 | 1570 | 1640 | 1800 | 2300 | 2800 | 1230 |
| 37129 | 1570 | 1640 | 1800 | 2300 | 2800 | 1230 |
| 37167 | 1430 | 1500 | 1640 | 2100 | 2560 | 1130 |
| 37127 | 1360 | 1420 | 1560 | 1990 | 2430 | 1070 |
| 37085 | 1320 | 1380 | 1520 | 1940 | 2360 | 1040 |
| 37130 | 1280 | 1340 | 1470 | 1880 | 2290 | 1010 |
| 37132 | 1280 | 1340 | 1470 | 1880 | 2290 | 1010 |
| 37118 | 1150 | 1170 | 1320 | 1660 | 2020 | 870 |
| 37149 | 1150 | 1180 | 1320 | 1660 | 2020 | 870 |
# ----------------------------------------------------------
# Install & load required packages
# ----------------------------------------------------------
if (!require("tidyverse"))
install.packages("tidyverse")
if (!require("gt"))
install.packages("gt")
library(tidyverse)
library(readxl)
library(gt)
# ----------------------------------------------------------
# Download HUD SAFMR Excel file
# ----------------------------------------------------------
download.file(
"https://www.huduser.gov/portal/datasets/fmr/fmr2026/fy2026_safmrs.xlsx",
"rent.xlsx",
mode = "wb"
)
# ----------------------------------------------------------
# Read Excel data
# ----------------------------------------------------------
FMR <- read_xlsx(path = "rent.xlsx", .name_repair = "universal")
# ----------------------------------------------------------
# Rutherford County ZIP Codes
# ----------------------------------------------------------
ZIPList <- c(
"37127", "37128", "37129", "37130", "37132",
"37085", "37118", "37149", "37037", "37153",
"37167", "37086"
)
# ----------------------------------------------------------
# Filter, select columns, and rename
# ----------------------------------------------------------
FMR_RuCo <- FMR %>%
filter(ZIP.Code %in% ZIPList) %>%
select(
ZIP.Code,
SAFMR.0BR,
SAFMR.1BR,
SAFMR.2BR,
SAFMR.3BR,
SAFMR.4BR
) %>%
distinct()
colnames(FMR_RuCo) <- c("ZIP", "Studio", "BR1", "BR2", "BR3", "BR4")
# ----------------------------------------------------------
# Add your code to this section
# ----------------------------------------------------------
FMR_RuCo <- FMR_RuCo %>%
mutate(Spread = round((BR4-Studio),0 )) %>%
arrange(desc(Spread))
# ----------------------------------------------------------
# Displaying the table, with the new columns
# ----------------------------------------------------------
FMR_RuCo_table <- gt(FMR_RuCo) %>%
tab_header(title = "Rutherford Rent Analysis") %>%
cols_align(align = "left")
FMR_RuCo_table