The data that I am using comes directly from the US Census Bureau. The number of multifamily permits is based on the number of Units that have been permited for more non single-family structures. This will be the sum of the the columns named
Data looks ready! :) The counties that did not have any multifamily permits have been removed from the data.
A pretty low average across the U.S. at only 81.376 in the month of June 2023. Very strong left skew towards the bottom
| County | total_mf_units |
|---|---|
| Harris County TX | 9439 |
| Maricopa County AZ | 8980 |
| Travis County TX | 7213 |
| Los Angeles County CA | 6941 |
| Miami-Dade County FL | 6842 |
| Davidson County TN | 4638 |
| King County WA | 4563 |
| Fulton County GA | 4560 |
| Mecklenburg County NC | 4364 |
| Bexar County TX | 4178 |
| Collin County TX | 4156 |
| Wake County NC | 3823 |
| Dallas County TX | 3618 |
| Duval County FL | 3530 |
| Salt Lake County UT | 3014 |
| Franklin County OH | 2675 |
| Denver County CO | 2648 |
| Hillsborough County FL | 2549 |
| Denton County TX | 2525 |
| San Bernardino County CA | 2520 |
This data set is at the county level. It contains the current level of permits for the particular month by county
data_1 %>%
left_join(FipsToState,by=c("FIPSState"="FIPS_Code"))%>%
group_by(Postal_Abbr.) %>%
summarise(MultifamilyPermits = sum(total_mf_units)) %>%
arrange(desc(MultifamilyPermits))-> State_Counts
knitr::kable(
State_Counts %>%
top_n(10,MultifamilyPermits),caption = "Top 10 Multifamily Permits in June 2023, Statewise"
)| Postal_Abbr. | MultifamilyPermits |
|---|---|
| TX | 44697 |
| FL | 37950 |
| CA | 27124 |
| NC | 16507 |
| CO | 11794 |
| GA | 11539 |
| WA | 11181 |
| AZ | 10385 |
| NJ | 10107 |
| NY | 8943 |
Only have FIPS codes, will convert over later.