How Many People Reside in Each Time Zone
I knew Eastern Time was the largest time zone population-wise, but I was curious how many people live in each Time Zone.
US Census 📍
📽️ Videos
How many households made less then $20,000 in 2024?
The most recent Census data available in May 2026 is from 2024. $20,000 a year even two years was pretty darn poor for household to live on, though many households do especially in the south.
| Rank | State | Households Making Under $20,000 |
|---|---|---|
| 1 | Puerto Rico | 40.18% |
| 2 | Mississippi | 18.08% |
| 3 | Louisiana | 17.45% |
| 4 | West Virginia | 16.26% |
| 5 | New Mexico | 15.95% |
| 6 | Kentucky | 15.41% |
| 7 | Arkansas | 15.27% |
| 8 | Alabama | 15.13% |
| 9 | Oklahoma | 13.56% |
| 10 | South Carolina | 13.21% |
| 11 | District of Columbia | 12.91% |
| 12 | New York | 12.78% |
| 13 | Tennessee | 12.74% |
| 14 | Ohio | 12.55% |
| 15 | Michigan | 12.23% |
| 16 | North Carolina | 12.20% |
| 17 | Missouri | 12.08% |
| 18 | Rhode Island | 12.08% |
| 19 | Georgia | 11.94% |
| 20 | Pennsylvania | 11.54% |
| 21 | Florida | 11.48% |
| 22 | Illinois | 11.46% |
| 23 | Indiana | 11.38% |
| 24 | Texas | 11.29% |
| 25 | Maine | 11.29% |
| 26 | North Dakota | 11.16% |
| 27 | Montana | 11.12% |
| 28 | Wyoming | 10.90% |
| 29 | Oregon | 10.75% |
| 30 | Nevada | 10.62% |
| 31 | Nebraska | 10.54% |
| 32 | Kansas | 10.52% |
| 33 | South Dakota | 10.49% |
| 34 | Massachusetts | 10.48% |
| 35 | Iowa | 10.46% |
| 36 | Arizona | 10.38% |
| 37 | Connecticut | 10.11% |
| 38 | Wisconsin | 9.96% |
| 39 | Vermont | 9.94% |
| 40 | California | 9.77% |
| 41 | Virginia | 9.46% |
| 42 | Delaware | 9.17% |
| 43 | Idaho | 9.12% |
| 44 | New Jersey | 9.04% |
| 45 | Minnesota | 9.03% |
| 46 | Hawaii | 8.97% |
| 47 | Maryland | 8.96% |
| 48 | Washington | 8.69% |
| 49 | Alaska | 8.69% |
| 50 | Colorado | 8.62% |
| 51 | New Hampshire | 7.86% |
| 52 | Utah | 6.97% |
Here is the simple R code to make this table using tidycensus and gt:
library(tidyverse)
library(tidycensus)
library(gt)
income <- get_acs(
geography = "state",
table = "B19001",
year = 2024,
output = "wide",
survey = "acs5",
geometry = FALSE);
income |>
select(ends_with('E'), -ends_with('001E')) |>
rowwise()|>
mutate(total = sum(across(matches('\\dE')))) |>
mutate(across(matches('\\dE'), \(x) x/total)) |>
transmute(State=NAME, `Households Making Under $20,000` = sum(across(c(B19001_002E, B19001_003E, B19001_004E)))) |>
ungroup() |>
arrange(desc(`Households Making Under $20,000`)) |>
mutate(Rank = row_number(), .before=1) |>
gt() |>
fmt_percent(3)
