vax <- read_csv("https://opendata.arcgis.com/datasets/f1ea9bbe3582447485b473d3c61e548c_0.csv?outSR=%7B%22latestWkid%22%3A6426%2C%22wkid%22%3A103008%7D")
## 
## -- Column specification --------------------------------------------------------
## cols(
##   X = col_double(),
##   Y = col_double(),
##   objectid = col_double(),
##   vaccine_field = col_character(),
##   count = col_double(),
##   pct_total = col_character(),
##   update_date = col_character()
## )

COVID-19 Vaccine

vax <- vax %>% select(group = vaccine_field, count, pct_total, date = update_date) 

vax$date <- as.Date(vax$date)

#NOW I NEED TO PARSE OUT AGE GROUPS, LOCATIONS, AND RACE

age <- c("0-9 years", "10-19 years", "20-29 years", "30-39 years", "40-49 years", "50-59 years", "60-69 years", "70-79 years", "80+ years", "Age Unknown")

age_vax <- vax %>% filter(group %in% age)


gen <- c("Female", "Male", "Gender Unknown")

gen_vax <- vax %>% filter( group %in% gen)

reg <- c("Central", "EasT", "North Coastal HHSA Region", "North Central", "North Inland", "South", "Other***", "Region Unknown")

reg_vax <- vax %>% filter(group %in% reg)

race <- c("Hispanic or Latino", "White", "Black or African-American", "Asian", "Native Hawaiian or Other Pacific Islander", "American Indian or Alaska Native", "Other Race", "Race/Ethnicity Unknown")

race_vax <- vax %>% filter(group %in% race)

#race_vax <- race_vax %>% arrange(desc(date))

#age_vax <- age_vax %>% arrange(desc(date))

#gen_vax <- gen_vax %>% arrange(desc(date))

THIS GETS THE POPULATION - I DIVIDE TOTAL SD POP (3,338,330) BY POP PERCENT

SOURCE

https://www.census.gov/quickfacts/fact/table/sandiegocountycalifornia,CA/PST045219