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 | 1900 | 1990 | 2180 | 2790 | 3400 |
| 37085 | 1320 | 1380 | 1520 | 1940 | 2360 |
| 37086 | 1730 | 1820 | 1990 | 2540 | 3100 |
| 37118 | 1150 | 1170 | 1320 | 1660 | 2020 |
| 37127 | 1360 | 1420 | 1560 | 1990 | 2430 |
| 37128 | 1570 | 1640 | 1800 | 2300 | 2800 |
| 37129 | 1570 | 1640 | 1800 | 2300 | 2800 |
| 37130 | 1280 | 1340 | 1470 | 1880 | 2290 |
| 37132 | 1280 | 1340 | 1470 | 1880 | 2290 |
| 37149 | 1150 | 1180 | 1320 | 1660 | 2020 |
| 37153 | 1670 | 1750 | 1920 | 2450 | 2990 |
| 37167 | 1430 | 1500 | 1640 | 2100 | 2560 |
library(tidyverse)
library(readxl)
library(gt)
FMR <- read_xlsx("rent.xlsx")
names(FMR) <- gsub("\\n", "_", names(FMR))
names(FMR) <- gsub(" ", "_", names(FMR))
ZIPList <- c(
"37127", "37128", "37129", "37130", "37132",
"37085", "37118", "37149", "37037", "37153",
"37167", "37086"
)
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")
# Create GT table
FMR_RuCo_table <- gt(FMR_RuCo) %>%
tab_header(title = "Rutherford FMR, by size and ZIP") %>%
cols_align(align = "left")
FMR_RuCo_table