library(tidyverse)
library(tidycensus)
library(zipcodeR)
install.packages("zipcodeR")
install.packages("units")


#install.packages("terra")
census_api_key(KEY, install = TRUE)
KEY <- '30e13ab22563318ff59286e433099f4174d4edd4'
#Ex
TRACTS <-get_tracts(search_city('Kemmerer','WY')$zipcode)  %>% full_join(get_tracts(search_city('Diamondville','WY')$zipcode))
get_decennial(geography="tract",variables=vars,state='WY',county='lincoln')

c('B01002_001E','B01002_002E','B01002_003E')
c('Median_Age','Median_Age_Male','Median_Age_Female')





get_acs(geography="tract",variables=vars,state='WY',county='lincoln',GEOID='56023978400')
######MALE

#Variable names from: https://api.census.gov/data/2019/acs/acs1/variables.html
sapply(1:25,function(x){paste0("B01001_00",x,"E")})
c(seq(0,15,by=5),18,20,21,22,seq(25,85,by=5))
c(seq(4,17,by=5),17,19,20,21,24,seq(29,84,by=5))
CODES <- read_csv("Data/API_CENSUS_CODES.csv") %>% mutate(Med_Age=(Min_Age+Max_Age)/2)
VARS <- CODES$Code

#Testing age Comparison between the two
TEMP <- get_acs(geography="tract",variables=VARS,state='WY',county='lincoln')
KEM <- TEMP %>% filter(GEOID=='56023978400')
KEM
19/sum(KEM$estimate)

LN <- TEMP %>% filter(GEOID!='56023978400')
LN
19/sum(KEM$estimate)