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| 1 | +#' American Community Survey 2019 |
| 2 | +#' |
| 3 | +#' Data for 3142 counties in the United States with many variables |
| 4 | +#' of the 2019 American Community Survey. |
| 5 | +#' |
| 6 | +#' |
| 7 | +#' @name county_2019 |
| 8 | +#' @docType data |
| 9 | +#' @format A data frame with 3142 observations on the following 95 variables. |
| 10 | +#' \describe{ |
| 11 | +#' \item{state}{State.} |
| 12 | +#' \item{name}{County name.} |
| 13 | +#' \item{fips}{FIPS code.} |
| 14 | +#' \item{median_individual_income}{Median individual income (2019).} |
| 15 | +#' \item{median_individual_income_moe}{Margin of error for \code{median_individual_income}.} |
| 16 | +#' \item{pop}{2019 population.} |
| 17 | +#' \item{pop_moe}{Margin of error for \code{pop}.} |
| 18 | +#' \item{white}{Percent of population that is white alone (2015-2019).} |
| 19 | +#' \item{white_moe}{Margin of error for \code{white}.} |
| 20 | +#' \item{black}{Percent of population that is black alone (2015-2019).} |
| 21 | +#' \item{black_moe}{Margin of error for \code{black}.} |
| 22 | +#' \item{native}{Percent of population that is Native American alone (2015-2019).} |
| 23 | +#' \item{native_moe}{Margin of error for \code{native}.} |
| 24 | +#' \item{asian}{Percent of population that is Asian alone (2015-2019).} |
| 25 | +#' \item{asian_moe}{Margin of error for \code{asian}.} |
| 26 | +#' \item{pac_isl}{Percent of population that is Native Hawaiian or other Pacific Islander alone (2015-2019).} |
| 27 | +#' \item{pac_isl_moe}{Margin of error for \code{pac_isl}.} |
| 28 | +#' \item{other_single_race}{Percent of population that is some other race alone (2015-2019).} |
| 29 | +#' \item{other_single_race_moe}{Margin of error for \code{other_single_race}.} |
| 30 | +#' \item{two_plus_races}{Percent of population that is two or more races (2015-2019).} |
| 31 | +#' \item{two_plus_races_moe}{Margin of error for \code{two_plus_races}.} |
| 32 | +#' \item{hispanic}{Percent of population that identifies as Hispanic or Latino (2015-2019).} |
| 33 | +#' \item{hispanic_moe}{Margin of error for \code{hispanic}.} |
| 34 | +#' \item{white_not_hispanic}{Percent of population that is white alone, not Hispanic or Latino (2015-2019).} |
| 35 | +#' \item{white_not_hispanic_moe}{Margin of error for \code{white_not_hispanic}.} |
| 36 | +#' \item{median_age}{Median age (2015-2019).} |
| 37 | +#' \item{median_age_moe}{Margin of error for \code{median_age}.} |
| 38 | +#' \item{age_under_5}{Percent of population under 5 (2015-2019).} |
| 39 | +#' \item{age_under_5_moe}{Margin of error for \code{age_under_5}.} |
| 40 | +#' \item{age_over_85}{Percent of population 85 and over (2015-2019).} |
| 41 | +#' \item{age_over_85_moe}{Margin of error for \code{age_over_85}.} |
| 42 | +#' \item{age_over_18}{Percent of population 18 and over (2015-2019).} |
| 43 | +#' \item{age_over_18_moe}{Margin of error for \code{age_over_18}.} |
| 44 | +#' \item{age_over_65}{Percent of population 65 and over (2015-2019).} |
| 45 | +#' \item{age_over_65_moe}{Margin of error for \code{age_over_65}.} |
| 46 | +#' \item{mean_work_travel}{Mean travel time to work (2015-2019).} |
| 47 | +#' \item{mean_work_travel_moe}{Margin of error for \code{mean_work_travel}.} |
| 48 | +#' \item{persons_per_household}{Persons per household (2015-2019)} |
| 49 | +#' \item{persons_per_household_moe}{Margin of error for \code{persons_per_household}.} |
| 50 | +#' \item{avg_family_size}{Average family size (2015-2019).} |
| 51 | +#' \item{avg_family_size_moe}{Margin of error for \code{avg_family_size}.} |
| 52 | +#' \item{housing_one_unit_structures}{Percent of housing units in 1-unit structures (2015-2019).} |
| 53 | +#' \item{housing_one_unit_structures_moe}{Margin of error for \code{housing_one_unit_structures}.} |
| 54 | +#' \item{housing_two_unit_structures}{Percent of housing units in multi-unit structures (2015-2019).} |
| 55 | +#' \item{housing_two_unit_structures_moe}{Margin of error for \code{housing_two_unit_structures}.} |
| 56 | +#' \item{housing_mobile_homes}{Percent of housing units in mobile homes and other types of units (2015-2019).} |
| 57 | +#' \item{housing_mobile_homes_moe}{Margin of error for \code{housing_mobile_homes}.} |
| 58 | +#' \item{median_individual_income_age_25plus}{Median individual income (2019 dollars, 2015-2019).} |
| 59 | +#' \item{median_individual_income_age_25plus_moe}{Margin of error for \code{median_individual_income_age_25plus}.} |
| 60 | +#' \item{hs_grad}{Percent of population 25 and older that is a high school graduate (2015-2019).} |
| 61 | +#' \item{hs_grad_moe}{Margin of error for \code{hs_grad}.} |
| 62 | +#' \item{bachelors}{Percent of population 25 and older that earned a Bachelor's degree or higher (2015-2019).} |
| 63 | +#' \item{bachelors_moe}{Margin of error for \code{bachelors}.} |
| 64 | +#' \item{households}{Total households (2015-2019).} |
| 65 | +#' \item{households_moe}{Margin of error for \code{households}.} |
| 66 | +#' \item{households_speak_spanish}{Percent of households speaking Spanish (2015-2019).} |
| 67 | +#' \item{households_speak_spanish_moe}{Margin of error for \code{households_speak_spanish}.} |
| 68 | +#' \item{households_speak_other_indo_euro_lang}{Percent of households speaking other Indo-European language (2015-2019).} |
| 69 | +#' \item{households_speak_other_indo_euro_lang_moe}{Margin of error for \code{households_speak_other_indo_euro_lang}.} |
| 70 | +#' \item{households_speak_asian_or_pac_isl}{Percent of households speaking Asian and Pacific Island language (2015-2019).} |
| 71 | +#' \item{households_speak_asian_or_pac_isl_moe}{Margin of error for \code{households_speak_asian_or_pac_isl}.} |
| 72 | +#' \item{households_speak_other}{Percent of households speaking non European or Asian/Pacific Island language (2015-2019).} |
| 73 | +#' \item{households_speak_other_moe}{Margin of error for \code{households_speak_other}.} |
| 74 | +#' \item{households_speak_limited_english}{Percent of limited English-speaking households (2015-2019).} |
| 75 | +#' \item{households_speak_limited_english_moe}{Margin of error for \code{households_speak_limited_english}.} |
| 76 | +#' \item{poverty}{Percent of population below the poverty level (2015-2019).} |
| 77 | +#' \item{poverty_moe}{Margin of error for \code{poverty}.} |
| 78 | +#' \item{poverty_under_18}{Percent of population under 18 below the poverty level (2015-2019).} |
| 79 | +#' \item{poverty_under_18_moe}{Margin of error for \code{poverty_under_18}.} |
| 80 | +#' \item{poverty_65_and_over}{Percent of population 65 and over below the poverty level (2015-2019).} |
| 81 | +#' \item{poverty_65_and_over_moe}{Margin of error for \code{poverty_65_and_over}.} |
| 82 | +#' \item{mean_household_income}{Mean household income (2019 dollars, 2015-2019).} |
| 83 | +#' \item{mean_household_income_moe}{Margin of error for \code{mean_household_income}.} |
| 84 | +#' \item{per_capita_income}{Per capita money income in past 12 months (2019 dollars, 2015-2019).} |
| 85 | +#' \item{per_capita_income_moe}{Margin of error for \code{per_capita_income}.} |
| 86 | +#' \item{median_household_income}{Median household income (2015-2019).} |
| 87 | +#' \item{median_household_income_moe}{Margin of error for \code{median_household_income}.} |
| 88 | +#' \item{veterans}{Percent among civilian population 18 and over that are veterans (2015-2019).} |
| 89 | +#' \item{veterans_moe}{Margin of error for \code{veterans}.} |
| 90 | +#' \item{unemployment_rate}{Unemployment rate among those ages 20-64 (2015-2019).} |
| 91 | +#' \item{unemployment_rate_moe}{Margin of error for \code{unemployment_rate}.} |
| 92 | +#' \item{uninsured}{Percent of civilian noninstitutionalized population that is uninsured (2015-2019).} |
| 93 | +#' \item{uninsured_moe}{Margin of error for \code{uninsured}.} |
| 94 | +#' \item{uninsured_under_6}{Percent of population under 6 years that is uninsured (2015-2019).} |
| 95 | +#' \item{uninsured_under_6_moe}{Margin of error for \code{uninsured_under_6}.} |
| 96 | +#' \item{uninsured_under_19}{Percent of population under 19 that is uninsured (2015-2019).} |
| 97 | +#' \item{uninsured_under_19_moe}{Margin of error for \code{uninsured_under_19}.} |
| 98 | +#' \item{uninsured_65_and_older}{Percent of population 65 and older that is uninsured (2015-2019).} |
| 99 | +#' \item{uninsured_65_and_older_moe}{Margin of error for \code{uninsured_65_and_older}.} |
| 100 | +#' \item{household_has_computer}{Percent of households that have desktop or laptop computer (2015-2019).} |
| 101 | +#' \item{household_has_computer_moe}{Margin of error for \code{household_has_computer}.} |
| 102 | +#' \item{household_has_smartphone}{Percent of households that have smartphone (2015-2019).} |
| 103 | +#' \item{household_has_smartphone_moe}{Margin of error for \code{household_has_smartphone}.} |
| 104 | +#' \item{household_has_broadband}{Percent of households that have broadband internet subscription (2015-2019).} |
| 105 | +#' \item{household_has_broadband_moe}{Margin of error for \code{household_has_broadband}.} |
| 106 | +#' } |
| 107 | +#' @source The data were downloaded via the \code{tidycensus} R package. |
| 108 | +#' @keywords datasets |
| 109 | +#' @seealso \code{\link{county}}, \code{\link{county_complete}} |
| 110 | +#' @examples |
| 111 | +#' |
| 112 | +#' library(ggplot2) |
| 113 | +#' |
| 114 | +#' ggplot(county_2019, |
| 115 | +#' aes(x = hs_grad, y = median_individual_income, |
| 116 | +#' size = sqrt(pop) / 1000)) + |
| 117 | +#' geom_point(alpha = 0.5) + |
| 118 | +#' scale_color_discrete(na.translate = FALSE) + |
| 119 | +#' guides(size = FALSE) + |
| 120 | +#' labs( |
| 121 | +#' x = "Percentage of population graduated from high school", |
| 122 | +#' y = "Median individual income" |
| 123 | +#' ) |
| 124 | +"county_2019" |
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