estatapi_example.R

pacman::p_load(
  sf,
  estatapi,
  tidyverse)


appId <- "*************************************"


res <- estat_getStatsData(
  appId = appId,
  statsDataId = "0000020201"
)
Name <- colnames(res)
Name[4] <- "Ａ人口世帯"
colnames(res) <- Name


Chiba <- res |> 
  filter(調査年 == "2020年度") |> 
  filter(substring(area_code, 1, 2) == "12") |> 
  filter(Ａ人口世帯 %in% c("A1405_0～5歳人口",
                      "A1303_65歳以上人口",
                      "A6101_従業も通学もしていない人口")) |> 
  select(code = area_code, type = Ａ人口世帯, value) |>
  mutate(value2 = lag(value, 60)) |> 
  mutate(value3 = lag(value2, 60)) |> 
  slice(-c(1:120)) |> 
  mutate(u5o65 = value2 + value3) |>
  mutate(ratio = value / u5o65) |> 
  select(code, ratio)



"%!in%" <- Negate("%in%")
NorthernTerr <- c("01695", "01696", "01697",
                  "01698", "01699", "01700")

JP_geo <- "https://github.com/igproj-fusion/R-gis/raw/main/ESRI_japan_84.geojson"
CHIBA <- read_sf(JP_geo) |> 
  filter(JCODE %!in% NorthernTerr) |>
  filter(SIKUCHOSON != "所属不明地") |> 
  filter(KEN == "千葉県")　|> 
  left_join(Chiba, by = c("JCODE" = "code"))



g <- ggplot()
g <- g + geom_sf(data = CHIBA, aes(fill = ratio))
g <- g + scale_fill_gradient(low = "#ffffcc", high = "#581100")
g <- g + labs(fill = "")
g <- g + theme_void()
print(g)