In cmhoove14/LEMMAABMv4: COVID ABM

knitr::opts_chunk$set(echo = TRUE)
knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())

library(tidyverse)
library(data.table)
library(tigris)
library(mapview)

sf_pop <- readRDS("data/processed/SF_agents_processed.rds")

  table(sf_pop$hhsize)
  table(sf_pop$hhincome)
  table(sf_pop$sex)
  table(sf_pop$age)
  table(sf_pop$occp)
  table(sf_pop$race)

  # SF_cts <- tigris::tracts("06", "075", year = 2018, class = "sf")
  SF_cts <- readRDS("data/processed/SF_cts_sf.rds")

  load("data/get/got/CA_SF_data2021-02-01.Rdata")

sf_pop_sum <- sf_pop %>% 
  group_by(geoid) %>% 
  summarise(Pop = n())


SF_pop_cts <- SF_cts %>% left_join(sf_pop_sum, by = c("GEOID" = "geoid"))

  mapview::mapview(SF_pop_cts, zcol = "Pop")

sf_pct_white <- sf_pop %>% 
  group_by(geoid) %>% 
  summarise(Pop = n(),
            White = sum(race == 1),
            pct_wht = White/Pop)


SF_pct_wht_cts <- SF_cts %>% left_join(sf_pct_white, by = c("GEOID" = "geoid"))

  mapview::mapview(SF_pct_wht_cts, zcol = "pct_wht")

sf_pct_hisp <- sf_pop %>% 
  group_by(geoid) %>% 
  summarise(Pop = n(),
            Hisp = sum(race == 8),
            pct_hisp = Hisp/Pop)


SF_pct_hisp_cts <- SF_cts %>% left_join(sf_pct_hisp, by = c("GEOID" = "geoid"))

  mapview::mapview(SF_pct_hisp_cts, zcol = "pct_hisp")

sf_pct_black <- sf_pop %>% 
  group_by(geoid) %>% 
  summarise(Pop = n(),
            Black = sum(race == 2),
            pct_black = Black/Pop)


SF_pct_black_cts <- SF_cts %>% left_join(sf_pct_black, by = c("GEOID" = "geoid"))

  mapview::mapview(SF_pct_black_cts, zcol = "pct_black")

sf_income <- sf_pop %>% 
  group_by(geoid) %>% 
  summarise(Mean_Income = mean(hhincome))


SF_income_cts <- SF_cts %>% left_join(sf_income, by = c("GEOID" = "geoid"))

  mapview::mapview(SF_income_cts, zcol = "Mean_Income")