I use tidycensus to collect demographic data but it seems something wrong since I got 0 female percentage for the zipcode 39309, 87040 and 78712. I also have the same problem, getting some zero values for bachelor's degree percentage, age percentage and population density
Here is my code for female percentage.
library(tidycensus)
library(tidyverse)
# Create the data frame
zipcode_df <- data.frame(as.character(c(39309, 87040, 78712)))
# Rename the column to "zipcode"
colnames(zipcode_df)[1] <- "zipcode"
# Display the result
print(zipcode_df)
# Set up Census key
census_api_key("94d96c1dfb04afe285d0db958f78ded8a4b197f7")
# Get total population and female population for all zip code tabulation areas (ZCTAs)
population_gender <- get_acs(
geography = "zcta",
variables = c("total_population" = "B01003_001E",
"female_population" = "B01001A_017"),
year = 2021,
survey = "acs5",
output = "wide"
) |>
mutate(zipcode = as.character(GEOID)) |>
select(zipcode, total_population, female_populationE) |>
rename(female_population = female_populationE)
# Calculate the percentage of male population
percentage_female_population <- population_gender %>%
mutate(percentage_female = (female_population / total_population) * 100) %>%
select(zipcode, percentage_female)
outcome <- zipcode_df |> left_join(percentage_female_population, by = "zipcode")
> outcome
zipcode percentage_female
1 39309 0
2 87040 0
3 78712 0