rural

2019-11-20-rural.R

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+library(sf)
+library(readxl)
+library(tigris)
+library(albersusa)
+library(hrbrthemes)
+library(tidyverse)
+
+farms <- read_excel(here::here("data/Ag_Census_Map_data_07172015.xlsx"), sheet = "Farms", col_names = TRUE)
+
+ffactor <- c("Less than 250", "250 - 499", "750 - 999", "500 - 749", "1,000 or more")
+
+counties_sf() %>%
+  mutate(fips = as.character(fips)) %>%
+  left_join(
+    select(farms, fips = FIPSTEXT, range = y12_M249_classRange),
+    by = "fips"
+  ) %>%
+  mutate(range = factor(range, ffactor)) -> farms_df
+
+ggplot() +
+  geom_sf(data = farms_df, aes(fill = range), color = "#b2b2b2", size = 0.1) +
+  scale_fill_brewer(
+    name = "# Farms", palette = "Greens", na.value = "white", labels = ffactor, breaks = ffactor
+  ) +
+  coord_sf(crs = albersusa::us_laea_proj, datum = NA) +
+  labs(
+    x = NULL, y = NULL,
+    title = "Down On The Farm: County-level Census of Agriculture Farms-per-County",
+    subtitle = "While the USDA does track some 'urban farms' most of the farmland is, indeed, rural.",
+    caption = "Data: USDA <www.nass.usda.gov/Publications/AgCensus/2012/Online_Resources/Ag_Census_Web_Maps/Data_download/index.php>; {tigris}\nhttps://git.rud.is/hrbrmstr/y2019-30daymapchallenge • #30DayMapChallenge"
+  ) +
+  theme_ipsum_es(grid="") +
+  theme(legend.position = c(0.985, 0.5))