structure(list(record_id = c(1, 2, 3, 4, 5), name_first = c("Nutmeg", 
"Tumtum", "Marcus", "Trudy", "John Lee"), name_last = c("Nutmouse", 
"Nutmouse", "Wood", "DAG", "Walker"), address = c(1001, 1002, 
1003, 1004, 1005), telephone = c("(405) 321-1111", "(405) 321-2222", 
"(405) 321-3333", "(405) 321-4444", "(405) 321-5555"), email = c("nutty@mouse.com", 
"tummy@mouse.comm", "mw@mwood.net", "peroxide@blonde.com", "left@hippocket.com"
), dob = structure(c(12294, 12121, -13051, -6269, -5375), class = "Date"), 
    sex = c(0, 1, 1, 0, 1), demographics_complete = c(2, 2, 2, 
    2, 2), height = c(7, 6, 180, 165, 193.04), weight = c(1, 
    1, 80, 54, 104), comments = c("Character in a book, with some guessing", 
    "A mouse character from a good book", "completely made up", 
    "This record doesn't have a DAG assigned\n\nSo call up Trudy on the telephone\nSend her a letter in the mail", 
    "Had a hand for trouble and a eye for cash\n\nHe had a gold watch chain and a black mustache"
    ), mugshot = c("mugshot-1.jpg", "mugshot-2.jpg", "mugshot-3.jpg", 
    "mugshot-4.jpg", "mugshot-5.jpg"), health_complete = c(1, 
    0, 2, 2, 0), race___1 = c(0, 0, 0, 0, 1), race___2 = c(0, 
    0, 0, 1, 0), race___3 = c(0, 1, 0, 0, 0), race___4 = c(0, 
    0, 1, 0, 0), race___5 = c(1, 1, 1, 1, 0), race___6 = c(0, 
    0, 0, 0, 1), ethnicity = c(1, 1, 0, 1, 2), race_and_ethnicity_complete = c(2, 
    0, 2, 2, 2)), row.names = c(NA, -5L), spec = structure(list(
    cols = list(record_id = structure(list(), class = c("collector_double", 
    "collector")), name_first = structure(list(), class = c("collector_character", 
    "collector")), name_last = structure(list(), class = c("collector_character", 
    "collector")), address = structure(list(), class = c("collector_double", 
    "collector")), telephone = structure(list(), class = c("collector_character", 
    "collector")), email = structure(list(), class = c("collector_character", 
    "collector")), dob = structure(list(format = ""), class = c("collector_date", 
    "collector")), age = structure(list(), class = c("collector_double", 
    "collector")), sex = structure(list(), class = c("collector_double", 
    "collector")), demographics_complete = structure(list(), class = c("collector_double", 
    "collector")), height = structure(list(), class = c("collector_double", 
    "collector")), weight = structure(list(), class = c("collector_double", 
    "collector")), bmi = structure(list(), class = c("collector_double", 
    "collector")), comments = structure(list(), class = c("collector_character", 
    "collector")), mugshot = structure(list(), class = c("collector_character", 
    "collector")), health_complete = structure(list(), class = c("collector_double", 
    "collector")), race___1 = structure(list(), class = c("collector_double", 
    "collector")), race___2 = structure(list(), class = c("collector_double", 
    "collector")), race___3 = structure(list(), class = c("collector_double", 
    "collector")), race___4 = structure(list(), class = c("collector_double", 
    "collector")), race___5 = structure(list(), class = c("collector_double", 
    "collector")), race___6 = structure(list(), class = c("collector_double", 
    "collector")), ethnicity = structure(list(), class = c("collector_double", 
    "collector")), race_and_ethnicity_complete = structure(list(), class = c("collector_double", 
    "collector"))), default = structure(list(), class = c("collector_guess", 
    "collector")), skip = 1L), class = "col_spec"), class = "data.frame")
