census <- structure(list(census_year = c(2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L ), state_fips_code = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 38L, 38L, 47L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 16L, 16L, 16L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 27L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 35L, 35L, 35L, 35L, 35L, 35L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 8L, 8L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 15L, 15L, 15L, 15L, 15L, 17L, 17L, 17L, 17L, 17L, 17L, 19L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 26L, 28L, 28L, 28L, 28L, 31L, 31L, 31L, 36L, 36L, 36L, 36L, 36L, 36L, 42L, 42L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 7L, 7L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 29L, 29L, 29L, 33L, 33L, 33L, 33L, 33L, 33L, 33L, 33L, 39L, 39L, 39L, 39L, 39L, 39L, 39L, 39L, 39L, 39L, 40L, 40L, 40L, 40L, 40L, 40L, 40L, 44L, 44L, 44L, 44L, 44L, 44L, 44L, 44L, 44L, 44L, 44L, 45L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 3L, 11L, 11L, 12L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 24L, 24L, 24L, 24L, 24L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 43L, 43L, 43L, 43L, 43L, 43L, 43L), .Label = c("Alabama", "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "Delaware", "District of Columbia", "Florida", "Georgia", "Hawaii", "Idaho", "Illinois", "Indiana", "Iowa", "Kansas", "Kentucky", "Louisiana", "Maine", "Maryland", "Massachusetts", "Michigan", "Minnesota", "Mississippi", "Missouri", "Montana", "Nebraska", "Nevada", "New Hampshire", "New Jersey", "New Mexico", "New York", "North Carolina", "Ohio", "Oklahoma", "Oregon", "Pennsylvania", "Rhode Island", "South Carolina", "Tennessee", "Texas", "Utah", "Virginia", "Washington", "West Virginia", "Wisconsin", "Wyoming"), class = "factor"), total_family_income = c(14550L, 22800L, 0L, 23000L, 48000L, 74000L, 23000L, 74000L, 60000L, 14600L, 0L, 37000L, 32000L, 113000L, 76900L, 100100L, 48000L, 48000L, 57200L, 43950L, 49000L, 31600L, 50090L, 64800L, 90000L, 38320L, 103700L, 0L, 70700L, 64800L, 60000L, 118100L, 21000L, 40000L, 17300L, 61300L, 0L, 6000L, 30270L, 8800L, 0L, 165000L, 15570L, 48630L, 13000L, 68020L, 130000L, 0L, NA, 12400L, 50400L, 65000L, 62900L, 31200L, 81710L, 37100L, 9500L, 25000L, 168200L, 168200L, 55300L, NA, NA, 17000L, 43000L, 18800L, 105000L, 48400L, 56000L, 88000L, 34900L, 0L, 106000L, 62820L, 55000L, 38000L, 37000L, 77600L, 40400L, 59700L, 75000L, 104000L, 44004L, 43000L, 146000L, 5500L, 63820L, 11200L, 34500L, 33600L, 52000L, 156000L, 59000L, 37500L, 67500L, 21800L, 79000L, 134000L, 77000L, 130000L, 10000L, 12000L, 101800L, 21000L, 43900L, 113710L, 82300L, 82300L, 80300L, 36100L, 60980L, 58760L, 35000L, 7400L, 141000L, 10200L, NA, 85400L, 77700L, 13500L, 24800L, 87100L, 47300L, 34850L, 62000L, 90000L, 18000L, 27500L, 57190L, 37600L, 9700L, 353100L, 7500L, 48000L, 65000L, 193000L, 60000L, 162600L, 41500L, 14900L, 103000L, 64800L, 44000L, 99600L, 18500L, 111850L, 102000L, 118000L, 0L, 30500L, 62400L, 378200L, 45000L, 158000L, 98000L, 13000L, 73020L, 20000L, 33300L, 34000L, 84000L, 12800L, 40600L, 154630L, 88000L, 42000L, 48790L, NA, 20300L, 30000L, 64890L, 38500L, 20600L, 42000L, 5800L, 40000L, 21200L, NA, 93500L, 42960L, 45400L, 9500L, 208100L, 95500L, 44500L, 360900L, 67050L, 4500L, 46600L, 22800L, 80000L, 36200L, 50000L, 73500L, 54240L, 79300L, 72020L, 52000L, 342000L, 122310L, 113000L, 14000L, 40750L, 50000L, 22000L, 72100L, 63130L, 20020L, 22990L, 12600L, 19604L, 13100L, 0L, 13400L, 79100L, 77000L, 10400L, 44200L, 65100L, 63000L, 80000L, 11900L, 61700L, 25100L, 70000L, 100000L, 40400L, 25700L, 97900L, 119000L, 29200L, 80000L, 45400L, 50030L, 44000L, 32000L, 32000L, 4600L, 56000L, 348000L, 27000L, 2800L, 9200L, 150500L, 237000L, NA, 9300L, 30100L, 40050L, 19200L, 37500L, 7600L, 141900L, 45800L, 22050L, 38000L, 32500L, 199000L, 51000L, 55000L, 59300L, 58000L, 22400L, 13000L, 21500L, 63600L, 0L, 11300L, 30000L, 125680L, 26700L, 12900L, 892050L, 49100L, NA, 0L, 80100L, 129300L, 48000L, 14300L, 35320L, 13900L, 93000L, 30100L, 6800L, 74200L, 100000L, 3800L, 458000L, 10700L, 34300L, 0L, 112500L, 116720L, 60700L, 51500L, 92000L, 31300L, 10250L, 89100L, 82700L, 33000L, 36000L, 0L, 28800L, 75330L, 23000L, 35900L, 0L, 94400L, 13800L, 9300L, 25900L, 24000L, 49300L, 627300L, 76500L, 15000L, 32500L, 46800L, 30000L, 0L, 51000L, 6000L, 45000L, 57000L, 46200L, 21100L, 42524L, 122000L, 40900L, 63740L, NA, 206700L, 145600L, 56740L, 47400L, 88200L, 35000L, 20000L, 26700L, 42700L, 21200L, 24000L, 23800L, 51400L, 49000L, 87880L, 57400L, 42000L, 77620L, 24900L, 69220L, 25980L, 92000L, 69000L, 20340L, 113500L, 48000L, 75000L, 55600L, 10000L, 92900L, 43010L, 46000L, 33200L, 17000L, 0L, 52500L, 52000L, 58000L, 61500L, 60720L, 12600L, 4800L, 13460L, 38000L, 39500L, 120000L, 52500L, 48300L, 111000L, 5000L, 22000L, 33100L, 86720L, 49900L, 53000L, 29600L, 54000L, 15000L, 148400L, 45800L, 84000L, 29000L, 25000L, 66400L, 11620L, 36400L, 12000L, 12300L, 18150L, 0L, 21500L, 48200L, 23600L, 17100L, 20000L, 0L, 72520L, 34500L, 38400L, 45000L, 50000L, 33780L, 175000L, 53000L, 5080L, 14620L, 10940L, 108484L, 44410L, 38800L, 42000L, 8000L, NA, 31500L, 36000L, 42900L, 5000L, 11580L, 78700L, 29340L, 77500L, 36000L, 130000L, 64500L, 62490L, 67300L, 25000L, 43000L, 13300L, 30900L, NA, 54090L, 146500L, 500L, 21700L, 10000L, 55800L, 0L, 8100L, 1400L, 39900L, 57700L, 3300L, NA, 16300L, 54000L, 36400L, 15600L, 9400L, 74000L, 25280L, 55500L, 22200L, 79100L, 75050L, 74490L, 20000L, 27150L, 40300L, 18600L, NA, 0L, 24000L, 24000L, 17900L, 32350L, 42300L, 17800L, 33000L, NA, 44000L, 24700L, 0L, 69000L, 60300L, 150000L, 171000L, 103000L, 51700L, 119800L, 18000L, 45100L, 8500L, 55400L, 15000L, NA, 39370L), age = c(44L, 20L, 20L, 6L, 55L, 43L, 60L, 47L, 54L, 58L, 33L, 51L, 62L, 8L, 25L, 44L, 28L, 1L, 31L, 69L, 31L, 80L, 2L, 47L, 12L, 47L, 8L, 67L, 17L, 69L, 55L, 18L, 66L, 58L, 21L, 52L, 18L, 2L, 26L, 82L, 46L, 63L, 83L, 35L, 1L, 2L, 54L, 36L, 28L, 7L, 21L, 1L, 17L, 29L, 14L, 33L, 16L, 40L, 34L, 6L, 49L, 17L, 37L, 2L, 40L, 10L, 61L, 24L, 23L, 16L, 36L, 7L, 32L, 19L, 81L, 47L, 72L, 2L, 46L, 27L, 2L, 10L, 30L, 39L, 12L, 73L, 40L, 60L, 43L, 7L, 40L, 65L, 80L, 46L, 3L, 6L, 26L, 58L, 48L, 62L, 22L, 52L, 60L, 3L, 21L, 30L, 58L, 5L, 20L, 18L, 45L, 20L, 28L, 19L, 60L, 75L, 22L, 58L, 52L, 58L, 24L, 46L, 43L, 41L, 47L, 40L, 24L, 13L, 41L, 4L, 77L, 60L, 7L, 35L, 52L, 72L, 31L, 45L, 79L, 16L, 41L, 37L, 26L, 8L, 6L, 8L, 60L, 4L, 22L, 49L, 4L, 52L, 47L, 39L, 34L, 23L, 49L, 21L, 56L, 62L, 40L, 62L, 37L, 50L, 20L, 15L, 39L, 87L, 78L, 35L, 48L, 41L, 51L, 24L, 21L, 25L, 51L, 25L, 32L, 40L, 29L, 54L, 69L, 2L, 40L, 6L, 38L, 46L, 54L, 73L, 38L, 31L, 32L, 14L, 38L, 46L, 25L, 35L, 40L, 17L, 55L, 70L, 24L, 6L, 29L, 52L, 56L, 69L, 15L, 65L, 50L, 11L, 37L, 12L, 40L, 21L, 75L, 53L, 10L, 27L, 33L, 2L, 57L, 12L, 21L, 45L, 15L, 4L, 49L, 48L, 52L, 14L, 64L, 46L, 35L, 27L, 45L, 21L, 63L, 36L, 29L, 5L, 0L, 45L, 45L, 36L, 15L, 4L, 35L, 17L, 49L, 6L, 43L, 46L, 5L, 37L, 4L, 14L, 45L, 44L, 39L, 23L, 12L, 20L, 12L, 54L, 52L, 70L, 27L, 16L, 30L, 48L, 46L, 35L, 56L, 52L, 16L, 32L, 47L, 61L, 6L, 10L, 48L, 29L, 30L, 66L, 37L, 60L, 57L, 39L, 82L, 18L, 24L, 48L, 36L, 15L, 39L, 31L, 23L, 75L, 39L, 8L, 29L, 6L, 5L, 11L, 28L, 70L, 46L, 12L, 9L, 2L, 61L, 31L, 7L, 10L, 36L, 29L, 9L, 53L, 60L, 67L, 27L, 10L, 48L, 8L, 85L, 57L, 39L, 52L, 38L, 13L, 40L, 10L, 37L, 53L, 40L, 4L, 27L, 28L, 30L, 45L, 59L, 67L, 5L, 13L, 15L, 16L, 1L, 6L, 35L, 71L, 48L, 18L, 46L, 40L, 2L, 44L, 31L, 35L, 26L, 46L, 54L, 2L, 37L, 42L, 69L, 81L, 16L, 10L, 10L, 57L, 18L, 24L, 30L, 8L, 25L, 4L, 35L, 60L, 5L, 53L, 40L, 4L, 78L, 60L, 52L, 42L, 7L, 26L, 34L, 73L, 27L, 40L, 22L, 26L, 18L, 39L, 49L, 27L, 23L, 30L, 39L, 64L, 71L, 2L, 4L, 18L, 87L, 31L, 63L, 78L, 29L, 10L, 30L, 61L, 40L, 21L, 9L, 6L, 49L, 54L, 60L, 5L, 85L, 35L, 29L, 33L, 73L, 20L, 76L, 37L, 57L, 29L, 26L, 8L, 40L, 9L, 7L, 70L, 37L, 71L, 49L, 44L, 31L, 74L, 10L, 71L, 54L, 4L, 54L, 93L, 32L, 46L, 45L, 3L, 31L, 70L, 41L, 3L, 44L, 81L, 12L, 81L, 17L, 30L, 10L, 5L, 42L, 3L, 1L, 29L, 61L, 36L, 25L, 41L, 9L, 10L, 13L, 3L, 15L, 32L, 68L, 32L, 32L, 24L, 18L, 41L, 6L, 38L, 43L, 76L, 24L, 36L, 5L, 68L, 12L, 60L, 60L, 47L), sex = structure(c(2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L), .Label = c("Female", "Male"), class = "factor"), race_general = structure(c(7L, 8L, 2L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 8L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 2L, 8L, 8L, 8L, 7L, 8L, 8L, 8L, 2L, 2L, 7L, 2L, 2L, 8L, 3L, 3L, 6L, 2L, 8L, 8L, 2L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 2L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 6L, 8L, 8L, 7L, 8L, 8L, 8L, 8L, 8L, 5L, 8L, 3L, 3L, 8L, 5L, 5L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 8L, 8L, 8L, 6L, 8L, 2L, 5L, 7L, 2L, 7L, 8L, 8L, 5L, 3L, 8L, 3L, 5L, 6L, 8L, 8L, 8L, 6L, 8L, 8L, 8L, 8L, 5L, 2L, 6L, 5L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 7L, 2L, 8L, 8L, 8L, 2L, 8L, 8L, 2L, 8L, 7L, 2L, 2L, 8L, 8L, 8L, 2L, 5L, 8L, 2L, 7L, 2L, 6L, 8L, 8L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 2L, 8L, 2L, 8L, 7L, 8L, 8L, 8L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 2L, 8L, 2L, 8L, 5L, 2L, 2L, 8L, 8L, 2L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 1L, 8L, 8L, 5L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 2L, 8L, 8L, 8L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 7L, 8L, 6L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 4L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 8L, 2L, 8L, 2L, 2L, 2L, 2L, 2L, 7L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 7L, 8L, 8L, 1L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 7L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 8L, 8L, 1L, 6L, 8L, 6L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 6L, 3L, 8L, 5L, 2L, 2L, 8L, 8L, 8L, 8L, 8L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 2L, 8L, 8L, 2L, 8L, 2L, 8L, 2L, 8L, 2L, 8L, 2L, 2L, 8L, 8L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L, 8L, 8L, 2L, 8L, 8L, 5L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 2L, 8L), .Label = c("American Indian or Alaska Native", "Black", "Chinese", "Japanese", "Other", "Other Asian or Pacific Islander", "Two major races", "White"), class = "factor"), marital_status = structure(c(3L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 6L, 4L, 1L, 1L, 4L, 4L, 3L, 3L, 4L, 3L, 3L, 3L, 6L, 4L, 4L, 4L, 3L, 4L, 6L, 4L, 1L, 3L, 4L, 3L, 3L, 4L, 3L, 4L, 4L, 3L, 6L, 1L, 3L, 6L, 3L, 4L, 4L, 3L, 4L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 3L, 4L, 3L, 4L, 4L, 4L, 3L, 4L, 1L, 3L, 4L, 4L, 3L, 4L, 3L, 4L, 6L, 3L, 6L, 4L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 1L, 3L, 1L, 3L, 4L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 1L, 3L, 4L, 2L, 3L, 6L, 4L, 1L, 3L, 3L, 4L, 3L, 4L, 3L, 4L, 4L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 4L, 3L, 4L, 4L, 4L, 4L, 3L, 3L, 4L, 3L, 3L, 3L, 3L, 3L, 6L, 4L, 3L, 5L, 3L, 4L, 4L, 4L, 3L, 4L, 4L, 3L, 4L, 3L, 1L, 3L, 3L, 4L, 3L, 4L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 4L, 2L, 2L, 3L, 1L, 4L, 1L, 3L, 4L, 4L, 4L, 4L, 2L, 3L, 4L, 3L, 4L, 3L, 4L, 3L, 4L, 4L, 1L, 3L, 3L, 3L, 1L, 4L, 4L, 1L, 3L, 4L, 3L, 3L, 4L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 3L, 4L, 1L, 6L, 4L, 4L, 4L, 3L, 3L, 6L, 1L, 4L, 4L, 3L, 4L, 3L, 4L, 4L, 3L, 4L, 4L, 4L, 3L, 3L, 4L, 3L, 3L, 3L, 1L, 3L, 4L, 3L, 3L, 4L, 4L, 4L, 1L, 3L, 4L, 4L, 4L, 1L, 4L, 2L, 4L, 4L, 4L, 4L, 3L, 4L, 4L, 3L, 1L, 3L, 3L, 4L, 4L, 4L, 3L, 6L, 6L, 4L, 4L, 4L, 1L, 3L, 2L, 4L, 1L, 4L, 3L, 3L, 1L, 4L, 4L, 3L, 3L, 3L, 3L, 2L, 6L, 3L, 4L, 6L, 4L, 4L, 3L, 3L, 4L, 3L, 3L, 4L, 3L, 3L, 4L, 3L, 4L, 4L, 4L, 4L, 3L, 1L, 4L, 4L, 4L, 3L, 4L, 4L, 4L, 3L, 4L, 4L, 2L, 6L, 6L, 3L, 4L, 3L, 4L, 6L, 3L, 4L, 3L, 3L, 4L, 2L, 4L, 3L, 1L, 3L, 4L, 4L, 2L, 4L, 1L, 6L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 3L, 4L, 4L, 3L, 3L, 3L, 3L, 4L, 3L, 4L, 4L, 4L, 6L, 6L, 4L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 4L, 3L, 1L, 4L, 3L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 4L, 3L, 3L, 5L, 4L, 4L, 4L, 3L, 4L, 3L, 4L, 6L, 3L, 4L, 4L, 4L, 6L, 3L, 1L, 4L, 3L, 4L, 4L, 3L, 1L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 6L, 4L, 3L, 1L, 4L, 4L, 6L, 3L, 2L, 3L, 3L, 4L, 1L, 4L, 4L, 6L, 3L, 6L, 3L, 2L, 3L, 3L, 4L, 4L, 3L, 4L, 1L, 6L, 4L, 3L, 3L, 4L, 4L, 3L, 4L, 4L, 1L, 6L, 4L, 3L, 4L, 3L, 4L, 4L, 3L, 4L, 4L, 3L, 4L, 2L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 3L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 3L, 4L, 3L, 4L, 1L, 4L, 6L, 2L, 3L), .Label = c("Divorced", "Married/spouse absent", "Married/spouse present", "Never married/single", "Separated", "Widowed"), class = "factor"), total_personal_income = c(0L, 13000L, 20000L, NA, 36000L, 27000L, 11800L, 48000L, 40000L, 14600L, 23000L, 37000L, 32000L, NA, 6000L, 16100L, 12000L, NA, 20000L, 4800L, 28000L, 31600L, NA, 49300L, NA, 34320L, NA, 8400L, 3700L, 4800L, 53000L, 7500L, 6000L, 0L, 4800L, 35000L, 2000L, NA, 24250L, 8800L, 17000L, 123000L, 15570L, 15830L, NA, NA, 64000L, 17500L, 0L, NA, 4000L, NA, 2000L, 10000L, NA, 37100L, 1800L, 25000L, 121600L, NA, 55300L, 2000L, 0L, NA, 0L, NA, 105000L, 0L, 0L, 0L, 19900L, NA, 22000L, 720L, 55000L, 38000L, 17300L, NA, 14200L, 14500L, NA, NA, 44004L, 43000L, NA, 3000L, 47950L, 11200L, 15300L, NA, 27000L, 10000L, 52100L, 17500L, NA, NA, 25000L, 134000L, 0L, 115000L, 10000L, 5100L, 4400L, NA, 9500L, 38400L, 0L, NA, 26300L, 0L, 0L, 4000L, 15000L, 5600L, 111000L, 10200L, 14100L, 32400L, 45000L, 0L, 18800L, 36000L, 28000L, 30000L, 34000L, 40000L, 3600L, NA, 57190L, NA, 9700L, 330000L, NA, 0L, 58000L, 20000L, 36000L, 160000L, 41500L, 0L, 75000L, 10300L, 1000L, NA, NA, NA, 0L, NA, 32000L, 0L, NA, 0L, 45000L, 50000L, 53000L, 28000L, 43020L, 8000L, 3000L, 34000L, 24000L, 0L, 40600L, 0L, 5000L, 0L, 22000L, 13000L, 1100L, 30000L, 63000L, 38500L, 6500L, 42000L, 484L, 40000L, 22460L, 19200L, 59700L, 44000L, 14000L, 1600L, 49700L, NA, 9500L, NA, 40000L, 4500L, 23000L, 14000L, 0L, 36200L, 25000L, NA, 8840L, 36000L, 24500L, 36000L, 317000L, 10L, 24000L, 4000L, 10000L, NA, 22000L, 47100L, 43030L, 4800L, 0L, 12600L, 19604L, NA, 22000L, NA, 23700L, 0L, 10400L, 44200L, NA, 12000L, 40000L, NA, 61700L, NA, 16000L, 50000L, 0L, NA, 72600L, 59000L, 4200L, NA, 8000L, 30030L, 16000L, 0L, 10000L, 4600L, 38000L, 15000L, 27000L, NA, NA, 150500L, 155000L, 90L, 0L, NA, 40050L, 0L, 0L, NA, 141900L, 45800L, NA, 0L, NA, NA, 20000L, 55000L, 26300L, 36000L, NA, 13000L, NA, -4400L, 0L, 5100L, 30000L, 17190L, 26700L, 100L, 446000L, 13000L, 3600L, 51000L, 0L, 34300L, 36000L, 14300L, NA, NA, 21000L, 24000L, 3500L, 23700L, 100000L, 3800L, 456000L, 10700L, 22700L, 0L, 37500L, 51500L, 60000L, 0L, 40000L, 0L, 12500L, 60900L, 32700L, NA, 36000L, NA, NA, NA, 23000L, 10600L, 44000L, NA, NA, NA, 0L, 24000L, NA, NA, 72600L, 15000L, NA, 30000L, 30000L, 0L, 14000L, NA, 45000L, NA, 9100L, 7600L, 10424L, 110000L, 2900L, NA, 25000L, NA, 46400L, 56740L, 23300L, NA, 35000L, 15000L, 16800L, 21000L, 21200L, 19700L, NA, NA, 0L, 480L, NA, NA, 76020L, 18900L, 37000L, 980L, 80900L, 69000L, NA, 86000L, 20000L, 17000L, 34100L, 0L, 43000L, NA, 46000L, 33200L, 17000L, 0L, 0L, NA, NA, 14700L, 980L, 3600L, 0L, NA, 28000L, NA, 60000L, 8200L, NA, 70000L, 5000L, NA, 26700L, 24100L, 9000L, 15000L, NA, 23000L, 12600L, 140900L, 12800L, 68000L, 9000L, 25000L, 15000L, 11620L, 50000L, 16000L, 4980L, 13500L, 0L, 15000L, 42600L, NA, NA, 0L, 0L, 39510L, 34500L, 38400L, 20000L, NA, 33780L, 55000L, 49100L, 6420L, NA, NA, 22000L, 34600L, 23000L, NA, 8000L, 0L, 6500L, 36000L, 38900L, 5000L, 11580L, 39920L, 29340L, 45500L, 0L, NA, 9000L, NA, NA, 15800L, 24000L, 13300L, 29800L, 0L, 6000L, 104800L, NA, 21700L, 0L, NA, 12100L, 8100L, 1400L, 25000L, 0L, NA, 25000L, 11800L, 54000L, NA, 14000L, 9400L, NA, 16300L, 0L, 15700L, NA, NA, 68020L, NA, NA, 2800L, 6700L, 6500L, 16000L, 24000L, NA, NA, NA, NA, 0L, 27000L, 9100L, 21000L, 9500L, 2200L, 15000L, 9100L, NA, 103000L, 68000L, 14500L, 22000L, 18000L, NA, 8500L, NA, 15000L, 48600L, 19800L)), row.names = c(NA, -500L), class = c("tbl_df", "tbl", "data.frame"))