用R语言再现这个图形是很容易的

library(tidyverse)

p <- states %>%
  rowwise() %>%
  reframe(x = c(-1, 0, 1, 1, 0, -1, -1) * 0.5 + x,
          y = c(0.25, 0.5, 0.25, -0.25, -0.5, -0.25, 0.25) * 2/sqrt(3) + y, 
          short, name, value) %>%
  ggplot(aes(x, y, fill = value, group = name)) +
  geom_polygon(linewidth = 2, color = "white") +
  geom_text(aes(label = short), data = states) +
  scale_fill_gradient(low = "#fffb77", high = "red", guide = "none") +
  coord_equal() +
  theme_void()

p

您可以使用plotly::ggplotly(p)轻松地将其转换为交互式绘图。
困难的部分是获取数据。我从链接页面上的JavaScript对象中提取了这个，并将其适当地转换为在R中使用：

states <- structure(list(short = c("AL", "AK", "AZ", "AR", "CA", "CO", 
"CT", "DE", "DC", "FL", "GA", "HI", "ID", "IL", "IN", "IA", "KS", 
"KY", "LA", "ME", "MD", "MA", "MI", "MN", "MS", "MO", "MT", "NE", 
"NV", "NH", "NJ", "NM", "NY", "NC", "ND", "OH", "OK", "OR", "PA", 
"RI", "SC", "SD", "TN", "TX", "UT", "VT", "VA", "WA", "WV", "WI", 
"WY"), name = c("Alabama", "Alaska", "Arizona", "Arkansas", "California", 
"Colorado", "Connecticut", "Delaware", "District of Columbia", 
"Florida", "Georgia", "Hawaii", "Idaho", "Illinois", "Indiana", 
"Iowa", "Kansas", "Kentucky", "Louisiana", "Maine", "Maryland", 
"Massachusetts", "Michigan", "Minnesota", "Mississippi", "Missouri", 
"Montana", "Nebraska", "Nevada", "New Hampshire", "New Jersey", 
"New Mexico", "New York", "North Carolina", "North Dakota", "Ohio", 
"Oklahoma", "Oregon", "Pennsylvania", "Rhode Island", "South Carolina", 
"South Dakota", "Tennessee", "Texas", "Utah", "Vermont", "Virginia", 
"Washington", "West Virginia", "Wisconsin", "Wyoming"), y = c(-5.19615242270663, 
0, -4.33012701892219, -4.33012701892219, -4.33012701892219, -3.46410161513775, 
-2.59807621135332, -3.46410161513775, -3.46410161513775, -6.92820323027551, 
-6.06217782649107, -6.92820323027551, -2.59807621135332, -2.59807621135332, 
-2.59807621135332, -2.59807621135332, -4.33012701892219, -3.46410161513775, 
-5.19615242270663, 0, -3.46410161513775, -1.73205080756888, -1.73205080756888, 
-1.73205080756888, -5.19615242270663, -3.46410161513775, -1.73205080756888, 
-3.46410161513775, -3.46410161513775, -0.866025403784439, -2.59807621135332, 
-5.19615242270663, -1.73205080756888, -4.33012701892219, -1.73205080756888, 
-2.59807621135332, -5.19615242270663, -3.46410161513775, -2.59807621135332, 
-1.73205080756888, -5.19615242270663, -2.59807621135332, -4.33012701892219, 
-6.06217782649107, -4.33012701892219, -0.866025403784439, -4.33012701892219, 
-1.73205080756888, -3.46410161513775, -1.73205080756888, -2.59807621135332
), x = c(7.5, 0.5, 3, 6, 2, 3.5, 11, 9.5, 10.5, 8.5, 8, 0.5, 
2, 6, 7, 5, 5, 6.5, 5.5, 11.5, 8.5, 10.5, 7.5, 4.5, 6.5, 5.5, 
2.5, 4.5, 2.5, 11, 10, 3.5, 9.5, 9, 3.5, 8, 4.5, 1.5, 9, 11.5, 
8.5, 4, 7, 4, 4, 10, 8, 1.5, 7.5, 5.5, 3), value = c(4849300L, 
737700L, 6745400L, 2994000L, 39250000L, 5540500L, 3596600L, 935600L, 
7288000L, 20612400L, 10310300L, 1419500L, 1634400L, 12801500L, 
6596800L, 3107100L, 2904000L, 4413400L, 4649600L, 1330000L, 6016400L, 
6811700L, 9928300L, 5519900L, 2984900L, 6093000L, 1023500L, 1881500L, 
2839000L, 1326800L, 8944400L, 2085500L, 19745200L, 10146700L, 
739400L, 11614370L, 3878000L, 3970200L, 12784200L, 1055100L, 
4832400L, 853100L, 6651100L, 27862500L, 2942900L, 626010L, 8411800L, 
7288000L, 1850320L, 5778700L, 584150L)), class = "data.frame", row.names = c(NA, 
51L))