library(tidyverse)
library(tidycensus)
library(haven)
fips_lbl <- fips_codes %>%
as_tibble() %>%
transmute(name = as.character(as.numeric(str_c(state_code, county_code))),
county_name = glue::glue("{str_remove(county, ' County')}, {state}"))
cps_all <- read_dta("data/input/cps/cps_00009.dta.gz")
count(cps_all, year)
count(cps_all, educ)
count_long <- function(var, tbl = cps_all) {
tbl %>%
count({{ var }}, year) %>%
rename(value = {{var}}) %>%
mutate(name = as.character(as_factor(value)),
value = zap_labels(value),
variable = quo_name(enquo(var))) %>%
select(variable, year, name, value, n)
}
cps_onewaytabs <- bind_rows(
count_long(sex),
cps_all %>%
mutate(age = as.integer(as.character(as_factor(age))),
age = ccesMRPprep::ccc_bin_age(age)) %>%
count_long(age, .),
count_long(race),
count_long(hispan),
count_long(educ),
count_long(voted),
count_long(statefip),
count_long(county) %>% left_join(fips_lbl, by = "name") %>% select(-name) %>% rename(name = county_name),
) %>%
mutate(name = as.character(name))
usethis::use_data(cps_onewaytabs, overwrite = TRUE)
# sex
# CPS NY - Bronx
cps_all %>%
filter(statefip == 36, year == 2016) %>%
select(wtfinl, age, sex, race, hispan, educ, voted) %>%
mutate(age = as.integer(as.character(as_factor(age))),
age = as_factor(ccc_bin_age(age))) %>%
filter(age == "25 to 34 years", educ %in% c(81, 91, 92, 111), race %in% c(100:200)) %>%
mutate(educ = case_when(educ %in% 81:92 ~ "Some College", educ %in% 111 ~ "4-year"),
voted = case_when(voted %in% 2 ~ "Voted", voted %in% 1 ~ "Did Not Vote", TRUE ~ "Other"),
hispan = case_when(hispan %in% 0 ~ "Non-Hispanic", hispan > 0 ~ "Hispanic"),
sex = as_factor(sex)) %>%
filter(hispan == "Non-Hispanic") %>%
count(age, sex, race, hispan, educ, voted) %>%
pivot_wider(id_cols = c(sex, race, hispan, educ),
names_from = voted,
values_from = n)
# ACS - NY-16
acs1 <- get_acs_cces(acscodes_age_sex_educ, year = 2016)
acs2 <- get_acs_cces(acscodes_age_sex_race, year = 2016)
acs1 %>% filter(cd == "NY-16", age == "25 to 34 years")
acs2 %>% filter(cd == "NY-16", age == "25 to 34 years") %>% filter(race %in% c("White", "Black"))
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