Given various features, the aim is to build a predictive model to determine the income level for people in US. The income levels are binned at below 50K and above 50K. Let’s think of some hypothesis which can influence the outcome. Here is a set of hypothesis to get us started:
Hò : There is no significant impact of the variables (below) on the dependent variable.
Ha : There exists a significant impact of the variables (below) on the dependent variable.
Age
Marital Status
Income
Family Members
No. of Dependents
Tax Paid
Investment (Mutual Fund, Stock)
Return from Investments
Education
Spouse Education
Nationality
Occupation
Region in US
Race
Occupation category
setwd("C:/Users/Shreyas Jadhav/Downloads")
usincome <- read.csv(paste("project.csv",sep="."))
View(usincome)
attach(usincome)
dim(usincome)## [1] 10000 41usincome$income_level[usincome$income_level == -50000] <- 'Below 50k'
usincome$income_level[usincome$income_level == 50000] <- 'Above 50k'summary(usincome)## age class_of_worker industry_code
## Min. : 0.00 Not in universe :4881 Min. : 0.00
## 1st Qu.:15.00 Private :3731 1st Qu.: 0.00
## Median :33.00 Self-employed-not incorporated: 409 Median : 2.00
## Mean :34.46 Local government : 407 Mean :15.82
## 3rd Qu.:49.00 State government : 245 3rd Qu.:33.00
## Max. :90.00 Federal government : 153 Max. :51.00
## (Other) : 174
## occupation_code education wage_per_hour
## Min. : 0.00 High school graduate :2454 Min. : 0.00
## 1st Qu.: 0.00 Children :2338 1st Qu.: 0.00
## Median : 2.00 Some college but no degree:1418 Median : 0.00
## Mean :11.65 Bachelors degree(BA AB BS): 973 Mean : 61.24
## 3rd Qu.:26.00 7th and 8th grade : 456 3rd Qu.: 0.00
## Max. :46.00 10th grade : 384 Max. :9000.00
## (Other) :1977
## enrolled_in_edu_inst_lastwk marital_status
## College or university: 286 Divorced : 653
## High school : 358 Married-A F spouse present : 28
## Not in universe :9356 Married-civilian spouse present:4274
## Married-spouse absent : 80
## Never married :4307
## Separated : 148
## Widowed : 510
## major_industry_code
## Not in universe or children :4898
## Retail trade : 891
## Education : 451
## Manufacturing-durable goods : 451
## Manufacturing-nondurable goods : 385
## Finance insurance and real estate: 331
## (Other) :2593
## major_occupation_code
## Not in universe :4898
## Adm support including clerical: 784
## Professional specialty : 700
## Executive admin and managerial: 638
## Other service : 628
## Sales : 627
## (Other) :1725
## race hispanic_origin
## Amer Indian Aleut or Eskimo: 118 All other :8672
## Asian or Pacific Islander : 309 Mexican-American : 401
## Black :1027 Mexican (Mexicano) : 362
## Other : 183 Central or South American: 195
## White :8363 Puerto Rican : 144
## (Other) : 195
## NA's : 31
## sex member_of_labor_union reason_for_unemployment
## Female:5312 No : 857 Job leaver : 30
## Male :4688 Not in universe:8996 Job loser - on layoff: 42
## Yes : 147 New entrant : 17
## Not in universe :9728
## Other job loser : 97
## Re-entrant : 86
##
## full_parttime_employment_stat capital_gains
## Children or Armed Forces :6156 Min. : 0.0
## Full-time schedules :2097 1st Qu.: 0.0
## Not in labor force :1314 Median : 0.0
## PT for non-econ reasons usually FT: 184 Mean : 395.4
## Unemployed full-time : 119 3rd Qu.: 0.0
## PT for econ reasons usually PT : 72 Max. :99999.0
## (Other) : 58
## capital_losses dividend_from_Stocks
## Min. : 0.00 Min. : 0.0
## 1st Qu.: 0.00 1st Qu.: 0.0
## Median : 0.00 Median : 0.0
## Mean : 39.81 Mean : 164.5
## 3rd Qu.: 0.00 3rd Qu.: 0.0
## Max. :4608.00 Max. :99999.0
##
## tax_filer_status region_of_previous_residence
## Head of household : 388 Abroad : 23
## Joint both 65+ : 397 Midwest : 200
## Joint both under 65 :3478 Northeast : 147
## Joint one under 65 & one 65+: 173 Not in universe:9218
## Nonfiler :3676 South : 225
## Single :1888 West : 187
##
## state_of_previous_residence
## Not in universe:9218
## California : 68
## Utah : 62
## North Carolina : 46
## Minnesota : 36
## (Other) : 524
## NA's : 46
## d_household_family_stat
## Householder :2689
## Child <18 never marr not in subfamily :2511
## Spouse of householder :2107
## Nonfamily householder :1104
## Child 18+ never marr Not in a subfamily: 575
## Secondary individual : 317
## (Other) : 697
## d_household_summary migration_msa
## Householder :3795 Nonmover :4088
## Child under 18 never married :2518 MSA to MSA : 534
## Spouse of householder :2107 NonMSA to nonMSA: 143
## Child 18 or older : 708 Not in universe : 87
## Other relative of householder: 472 MSA to nonMSA : 39
## Nonrelative of householder : 393 (Other) : 66
## (Other) : 7 NA's :5043
## migration_reg migration_within_reg
## Nonmover :4088 Nonmover :4088
## Same county : 506 Same county : 506
## Different county same state: 133 Different county same state: 133
## Not in universe : 87 Not in universe : 87
## Different region : 61 Different state in South : 45
## (Other) : 82 (Other) : 98
## NA's :5043 NA's :5043
## live_1_year_ago migration_sunbelt
## No : 782 No : 519
## Not in universe under 1 year old:5130 Not in universe:4175
## Yes :4088 Yes : 263
## NA's :5043
##
##
##
## num_person_Worked_employer family_members_under_18
## Min. :0.000 Both parents present :1921
## 1st Qu.:0.000 Father only present : 82
## Median :1.000 Mother only present : 676
## Mean :2.027 Neither parent present: 83
## 3rd Qu.:4.000 Not in universe :7238
## Max. :6.000
##
## country_father country_mother country_self
## United-States:8011 United-States:8065 United-States:8873
## Mexico : 484 Mexico : 488 Mexico : 278
## Puerto-Rico : 122 Puerto-Rico : 117 Puerto-Rico : 62
## Italy : 103 Italy : 87 Germany : 51
## Germany : 77 Germany : 74 Cuba : 46
## (Other) : 904 (Other) : 886 (Other) : 537
## NA's : 299 NA's : 283 NA's : 153
## citizenship
## Foreign born- Not a citizen of U S : 675
## Foreign born- U S citizen by naturalization: 298
## Native- Born abroad of American Parent(s) : 88
## Native- Born in Puerto Rico or U S Outlying: 66
## Native- Born in the United States :8873
##
##
## business_or_self_employed fill_questionnaire_veteran_admin
## Min. :0.0000 No : 84
## 1st Qu.:0.0000 Not in universe:9895
## Median :0.0000 Yes : 21
## Mean :0.1724
## 3rd Qu.:0.0000
## Max. :2.0000
##
## veterans_benefits weeks_worked_in_year year income_level
## Min. :0.000 Min. : 0.00 Min. :94.0 Length:10000
## 1st Qu.:2.000 1st Qu.: 0.00 1st Qu.:94.0 Class :character
## Median :2.000 Median :12.00 Median :95.0 Mode :character
## Mean :1.522 Mean :23.78 Mean :94.5
## 3rd Qu.:2.000 3rd Qu.:52.00 3rd Qu.:95.0
## Max. :2.000 Max. :52.00 Max. :95.0
## library(psych)
describe(usincome)[,0:9]## Warning in describe(usincome): NAs introduced by coercion## Warning in FUN(newX[, i], ...): no non-missing arguments to min; returning
## Inf## Warning in FUN(newX[, i], ...): no non-missing arguments to max; returning
## -Inf## vars n mean sd median trimmed
## age 1 10000 34.46 22.07 33 33.27
## class_of_worker* 2 10000 4.50 1.13 4 4.44
## industry_code 3 10000 15.82 18.11 2 14.16
## occupation_code 4 10000 11.65 14.52 2 9.70
## education* 5 10000 11.09 4.11 11 11.45
## wage_per_hour 6 10000 61.25 299.35 0 0.00
## enrolled_in_edu_inst_lastwk* 7 10000 2.91 0.38 3 3.00
## marital_status* 8 10000 3.98 1.41 4 4.00
## major_industry_code* 9 10000 13.99 4.83 15 14.30
## major_occupation_code* 10 10000 7.30 3.16 7 7.25
## race* 11 10000 4.64 0.87 5 4.86
## hispanic_origin* 12 9969 1.66 1.85 1 1.07
## sex* 13 10000 1.47 0.50 1 1.46
## member_of_labor_union* 14 10000 1.93 0.31 2 2.00
## reason_for_unemployment* 15 10000 4.01 0.30 4 4.00
## full_parttime_employment_stat* 16 10000 1.70 1.20 1 1.45
## capital_gains 17 10000 395.41 4271.33 0 0.00
## capital_losses 18 10000 39.81 281.44 0 0.00
## dividend_from_Stocks 19 10000 164.53 1860.00 0 0.04
## tax_filer_status* 20 10000 4.20 1.39 5 4.27
## region_of_previous_residence* 21 10000 4.00 0.46 4 4.00
## state_of_previous_residence* 22 9954 35.15 5.04 36 36.00
## d_household_family_stat* 23 10000 13.90 9.15 14 13.75
## d_household_summary* 24 10000 4.98 2.07 5 5.02
## migration_msa* 25 4957 4.90 0.97 5 4.96
## migration_reg* 26 4957 6.05 1.03 6 6.03
## migration_within_reg* 27 4957 7.00 1.19 7 7.03
## live_1_year_ago* 28 10000 2.33 0.61 2 2.39
## migration_sunbelt* 29 4957 1.95 0.39 2 1.99
## num_person_Worked_employer 30 10000 2.03 2.39 1 1.78
## family_members_under_18* 31 10000 4.06 1.60 5 4.33
## country_father* 32 9701 36.67 8.55 40 39.09
## country_mother* 33 9717 36.79 8.34 40 39.15
## country_self* 34 9847 38.12 6.65 40 40.00
## citizenship* 35 10000 4.62 1.11 5 4.98
## business_or_self_employed 36 10000 0.17 0.55 0 0.00
## fill_questionnaire_veteran_admin* 37 10000 1.99 0.10 2 2.00
## veterans_benefits 38 10000 1.52 0.85 2 1.65
## weeks_worked_in_year 39 10000 23.78 24.39 12 23.22
## year 40 10000 94.50 0.50 95 94.51
## income_level* 41 10000 NaN NA NA NaN
## mad min max
## age 25.20 0 90
## class_of_worker* 1.48 1 9
## industry_code 2.97 0 51
## occupation_code 2.97 0 46
## education* 2.97 1 17
## wage_per_hour 0.00 0 9000
## enrolled_in_edu_inst_lastwk* 0.00 1 3
## marital_status* 1.48 1 7
## major_industry_code* 1.48 1 24
## major_occupation_code* 1.48 1 15
## race* 0.00 1 5
## hispanic_origin* 0.00 1 9
## sex* 0.00 1 2
## member_of_labor_union* 0.00 1 3
## reason_for_unemployment* 0.00 1 6
## full_parttime_employment_stat* 0.00 1 8
## capital_gains 0.00 0 99999
## capital_losses 0.00 0 4608
## dividend_from_Stocks 0.00 0 99999
## tax_filer_status* 1.48 1 6
## region_of_previous_residence* 0.00 1 6
## state_of_previous_residence* 0.00 1 50
## d_household_family_stat* 14.83 1 27
## d_household_summary* 2.97 1 8
## migration_msa* 0.00 1 9
## migration_reg* 0.00 1 8
## migration_within_reg* 0.00 1 9
## live_1_year_ago* 0.00 1 3
## migration_sunbelt* 0.00 1 3
## num_person_Worked_employer 1.48 0 6
## family_members_under_18* 0.00 1 5
## country_father* 0.00 1 42
## country_mother* 0.00 1 42
## country_self* 0.00 1 42
## citizenship* 0.00 1 5
## business_or_self_employed 0.00 0 2
## fill_questionnaire_veteran_admin* 0.00 1 3
## veterans_benefits 0.00 0 2
## weeks_worked_in_year 17.79 0 52
## year 0.00 94 95
## income_level* NA Inf -Inftable(age)## age
## 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
## 147 161 149 160 150 149 146 144 146 171 184 170 166 138 157 176 160 125
## 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
## 110 139 126 102 121 120 152 146 132 144 145 160 155 161 149 181 161 168
## 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53
## 169 191 170 154 153 176 159 155 143 153 158 146 111 105 114 108 117 105
## 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
## 88 91 75 94 70 75 71 83 85 93 77 76 70 81 51 56 56 60
## 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89
## 50 70 66 48 47 41 59 40 42 28 35 27 27 21 19 16 12 9
## 90
## 33table(age!=0)##
## FALSE TRUE
## 147 9853prop.table(table(age!=0 & wage_per_hour!=0))*100##
## FALSE TRUE
## 93.85 6.15table(class_of_worker)## class_of_worker
## Federal government Local government
## 153 407
## Never worked Not in universe
## 17 4881
## Private Self-employed-incorporated
## 3731 148
## Self-employed-not incorporated State government
## 409 245
## Without pay
## 9table(class_of_worker!="Not in universe")##
## FALSE TRUE
## 4881 5119table(education)## education
## 10th grade
## 384
## 11th grade
## 318
## 12th grade no diploma
## 84
## 1st 2nd 3rd or 4th grade
## 96
## 5th or 6th grade
## 135
## 7th and 8th grade
## 456
## 9th grade
## 322
## Associates degree-academic program
## 218
## Associates degree-occup /vocational
## 261
## Bachelors degree(BA AB BS)
## 973
## Children
## 2338
## Doctorate degree(PhD EdD)
## 69
## High school graduate
## 2454
## Less than 1st grade
## 39
## Masters degree(MA MS MEng MEd MSW MBA)
## 347
## Prof school degree (MD DDS DVM LLB JD)
## 88
## Some college but no degree
## 1418prop.table(table(age!=0 & class_of_worker!="Not in universe"))*100##
## FALSE TRUE
## 48.81 51.19table(industry_code)## industry_code
## 0 1 2 3 4 5 6 7 8 9 11 12 13 14 15
## 4898 39 115 25 308 27 25 19 23 59 97 56 50 16 19
## 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
## 28 9 23 82 1 26 50 34 86 53 10 37 6 218 55
## 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45
## 56 192 891 153 178 59 207 61 147 90 187 246 451 125 218
## 46 47 48 49 50 51
## 8 69 36 38 92 2prop.table(table(industry_code & wage_per_hour!=0))*100##
## FALSE TRUE
## 93.85 6.15prop.table(table(citizenship))*100## citizenship
## Foreign born- Not a citizen of U S
## 6.75
## Foreign born- U S citizen by naturalization
## 2.98
## Native- Born abroad of American Parent(s)
## 0.88
## Native- Born in Puerto Rico or U S Outlying
## 0.66
## Native- Born in the United States
## 88.73NOTE: The income levels are binned at below 50K and above 50K.
Variable: income_level
-50,000 -> income level below 50k
+50,000 -> income level above 50k
age_and_education<-as.data.frame(table(age,education))
c1<-cut(as.numeric(as.character(age_and_education$age)),breaks=seq(0,90,by=10))
table(age_and_education$education,c1)## c1
## (0,10] (10,20] (20,30] (30,40]
## 10th grade 10 10 10 10
## 11th grade 10 10 10 10
## 12th grade no diploma 10 10 10 10
## 1st 2nd 3rd or 4th grade 10 10 10 10
## 5th or 6th grade 10 10 10 10
## 7th and 8th grade 10 10 10 10
## 9th grade 10 10 10 10
## Associates degree-academic program 10 10 10 10
## Associates degree-occup /vocational 10 10 10 10
## Bachelors degree(BA AB BS) 10 10 10 10
## Children 10 10 10 10
## Doctorate degree(PhD EdD) 10 10 10 10
## High school graduate 10 10 10 10
## Less than 1st grade 10 10 10 10
## Masters degree(MA MS MEng MEd MSW MBA) 10 10 10 10
## Prof school degree (MD DDS DVM LLB JD) 10 10 10 10
## Some college but no degree 10 10 10 10
## c1
## (40,50] (50,60] (60,70] (70,80]
## 10th grade 10 10 10 10
## 11th grade 10 10 10 10
## 12th grade no diploma 10 10 10 10
## 1st 2nd 3rd or 4th grade 10 10 10 10
## 5th or 6th grade 10 10 10 10
## 7th and 8th grade 10 10 10 10
## 9th grade 10 10 10 10
## Associates degree-academic program 10 10 10 10
## Associates degree-occup /vocational 10 10 10 10
## Bachelors degree(BA AB BS) 10 10 10 10
## Children 10 10 10 10
## Doctorate degree(PhD EdD) 10 10 10 10
## High school graduate 10 10 10 10
## Less than 1st grade 10 10 10 10
## Masters degree(MA MS MEng MEd MSW MBA) 10 10 10 10
## Prof school degree (MD DDS DVM LLB JD) 10 10 10 10
## Some college but no degree 10 10 10 10
## c1
## (80,90]
## 10th grade 10
## 11th grade 10
## 12th grade no diploma 10
## 1st 2nd 3rd or 4th grade 10
## 5th or 6th grade 10
## 7th and 8th grade 10
## 9th grade 10
## Associates degree-academic program 10
## Associates degree-occup /vocational 10
## Bachelors degree(BA AB BS) 10
## Children 10
## Doctorate degree(PhD EdD) 10
## High school graduate 10
## Less than 1st grade 10
## Masters degree(MA MS MEng MEd MSW MBA) 10
## Prof school degree (MD DDS DVM LLB JD) 10
## Some college but no degree 10mytable<-xtabs(~race+age,data=usincome)
mytable## age
## race 0 1 2 3 4 5 6 7 8 9 10
## Amer Indian Aleut or Eskimo 2 5 2 2 3 2 2 2 1 2 6
## Asian or Pacific Islander 5 5 5 7 1 6 7 6 10 6 5
## Black 23 23 19 18 18 23 15 22 15 20 28
## Other 3 8 3 3 7 7 6 6 7 4 3
## White 114 120 120 130 121 111 116 108 113 139 142
## age
## race 11 12 13 14 15 16 17 18 19 20 21
## Amer Indian Aleut or Eskimo 8 2 1 2 4 3 1 1 0 1 0
## Asian or Pacific Islander 3 7 7 2 6 3 2 4 5 3 6
## Black 23 19 16 16 36 21 16 15 17 19 13
## Other 1 6 3 2 3 5 4 3 1 1 0
## White 135 132 111 135 127 128 102 87 116 102 83
## age
## race 22 23 24 25 26 27 28 29 30 31 32
## Amer Indian Aleut or Eskimo 1 2 2 0 5 0 2 2 1 2 0
## Asian or Pacific Islander 7 5 6 4 2 5 7 7 4 7 5
## Black 10 11 16 16 7 16 18 27 13 13 19
## Other 6 6 2 5 4 5 2 7 2 5 3
## White 97 96 126 121 114 118 116 117 135 134 122
## age
## race 33 34 35 36 37 38 39 40 41 42 43
## Amer Indian Aleut or Eskimo 2 0 2 3 1 7 1 1 2 2 2
## Asian or Pacific Islander 7 5 8 6 6 3 5 7 6 4 4
## Black 21 18 8 9 13 18 18 12 13 18 12
## Other 1 1 2 1 1 3 3 3 2 1 4
## White 150 137 148 150 170 139 127 130 153 134 133
## age
## race 44 45 46 47 48 49 50 51 52 53 54
## Amer Indian Aleut or Eskimo 2 0 1 2 2 0 2 2 1 2 1
## Asian or Pacific Islander 5 8 8 2 4 1 6 2 3 4 3
## Black 15 14 11 14 4 10 12 9 10 8 7
## Other 3 3 1 4 0 2 1 2 2 0 0
## White 118 128 137 124 101 92 93 93 101 91 77
## age
## race 55 56 57 58 59 60 61 62 63 64 65
## Amer Indian Aleut or Eskimo 1 1 0 0 1 0 2 1 1 0 1
## Asian or Pacific Islander 5 3 1 1 1 2 2 0 2 1 1
## Black 8 13 6 8 6 3 8 8 7 4 8
## Other 1 0 0 0 1 1 0 0 2 0 0
## White 76 58 87 61 66 65 71 76 81 72 66
## age
## race 66 67 68 69 70 71 72 73 74 75 76
## Amer Indian Aleut or Eskimo 1 0 0 0 1 0 0 0 1 0 0
## Asian or Pacific Islander 1 1 0 1 1 0 1 0 2 0 0
## Black 2 5 3 6 3 4 4 4 6 4 4
## Other 0 2 0 0 0 0 1 0 1 0 0
## White 66 73 48 49 51 56 44 66 56 44 43
## age
## race 77 78 79 80 81 82 83 84 85 86 87
## Amer Indian Aleut or Eskimo 0 0 0 0 0 0 0 0 0 0 0
## Asian or Pacific Islander 1 1 1 0 0 1 1 0 0 0 1
## Black 1 5 1 2 4 3 2 5 1 0 0
## Other 0 0 0 0 1 0 0 0 0 0 0
## White 39 53 38 40 23 31 24 22 20 19 15
## age
## race 88 89 90
## Amer Indian Aleut or Eskimo 0 0 0
## Asian or Pacific Islander 0 0 0
## Black 0 0 4
## Other 0 0 0
## White 12 9 29mytable1<-xtabs(~class_of_worker+marital_status,data=usincome)
mytable1## marital_status
## class_of_worker Divorced Married-A F spouse present
## Federal government 22 2
## Local government 42 2
## Never worked 0 0
## Not in universe 145 11
## Private 371 10
## Self-employed-incorporated 8 0
## Self-employed-not incorporated 33 2
## State government 32 1
## Without pay 0 0
## marital_status
## class_of_worker Married-civilian spouse present
## Federal government 93
## Local government 279
## Never worked 2
## Not in universe 1237
## Private 2085
## Self-employed-incorporated 117
## Self-employed-not incorporated 311
## State government 145
## Without pay 5
## marital_status
## class_of_worker Married-spouse absent Never married
## Federal government 3 25
## Local government 3 61
## Never worked 0 15
## Not in universe 19 3017
## Private 51 1061
## Self-employed-incorporated 0 21
## Self-employed-not incorporated 3 42
## State government 1 61
## Without pay 0 4
## marital_status
## class_of_worker Separated Widowed
## Federal government 2 6
## Local government 7 13
## Never worked 0 0
## Not in universe 41 411
## Private 92 61
## Self-employed-incorporated 1 1
## Self-employed-not incorporated 4 14
## State government 1 4
## Without pay 0 0mytable2<-xtabs(~major_industry_code+income_level,data=usincome)
mytable2## income_level
## major_industry_code Above 50k Below 50k
## Agriculture 11 143
## Armed Forces 0 2
## Business and repair services 27 241
## Communications 10 45
## Construction 24 284
## Education 53 398
## Entertainment 5 85
## Finance insurance and real estate 54 277
## Forestry and fisheries 0 8
## Hospital services 26 161
## Manufacturing-durable goods 79 372
## Manufacturing-nondurable goods 44 341
## Medical except hospital 22 224
## Mining 4 21
## Not in universe or children 36 4862
## Other professional services 48 170
## Personal services except private HH 4 143
## Private household services 0 59
## Public administration 31 204
## Retail trade 38 853
## Social services 2 123
## Transportation 29 189
## Utilities and sanitary services 20 36
## Wholesale trade 20 172prop.table(table(major_industry_code,sex))*100## sex
## major_industry_code Female Male
## Agriculture 0.39 1.15
## Armed Forces 0.00 0.02
## Business and repair services 1.01 1.67
## Communications 0.24 0.31
## Construction 0.34 2.74
## Education 3.16 1.35
## Entertainment 0.46 0.44
## Finance insurance and real estate 2.01 1.30
## Forestry and fisheries 0.00 0.08
## Hospital services 1.43 0.44
## Manufacturing-durable goods 1.25 3.26
## Manufacturing-nondurable goods 1.71 2.14
## Medical except hospital 2.03 0.43
## Mining 0.02 0.23
## Not in universe or children 28.18 20.80
## Other professional services 1.19 0.99
## Personal services except private HH 0.98 0.49
## Private household services 0.53 0.06
## Public administration 1.06 1.29
## Retail trade 4.61 4.30
## Social services 1.05 0.20
## Transportation 0.70 1.48
## Utilities and sanitary services 0.08 0.48
## Wholesale trade 0.69 1.23prop.table(table(major_industry_code,migration_msa))*100## migration_msa
## major_industry_code Abroad to MSA Abroad to nonMSA
## Agriculture 0.00000000 0.00000000
## Armed Forces 0.00000000 0.00000000
## Business and repair services 0.00000000 0.00000000
## Communications 0.00000000 0.00000000
## Construction 0.04034698 0.00000000
## Education 0.00000000 0.00000000
## Entertainment 0.00000000 0.00000000
## Finance insurance and real estate 0.00000000 0.00000000
## Forestry and fisheries 0.00000000 0.00000000
## Hospital services 0.00000000 0.00000000
## Manufacturing-durable goods 0.04034698 0.00000000
## Manufacturing-nondurable goods 0.02017349 0.00000000
## Medical except hospital 0.00000000 0.00000000
## Mining 0.00000000 0.00000000
## Not in universe or children 0.20173492 0.04034698
## Other professional services 0.02017349 0.00000000
## Personal services except private HH 0.00000000 0.00000000
## Private household services 0.02017349 0.00000000
## Public administration 0.00000000 0.00000000
## Retail trade 0.00000000 0.04034698
## Social services 0.00000000 0.00000000
## Transportation 0.02017349 0.00000000
## Utilities and sanitary services 0.00000000 0.00000000
## Wholesale trade 0.02017349 0.00000000
## migration_msa
## major_industry_code MSA to MSA MSA to nonMSA
## Agriculture 0.04034698 0.00000000
## Armed Forces 0.02017349 0.00000000
## Business and repair services 0.30260238 0.12104095
## Communications 0.08069397 0.00000000
## Construction 0.48416381 0.04034698
## Education 0.58503127 0.00000000
## Entertainment 0.12104095 0.00000000
## Finance insurance and real estate 0.36312286 0.00000000
## Forestry and fisheries 0.04034698 0.00000000
## Hospital services 0.16138794 0.00000000
## Manufacturing-durable goods 0.50433730 0.06052048
## Manufacturing-nondurable goods 0.42364333 0.04034698
## Medical except hospital 0.30260238 0.02017349
## Mining 0.02017349 0.00000000
## Not in universe or children 4.47851523 0.40346984
## Other professional services 0.22190841 0.00000000
## Personal services except private HH 0.24208190 0.02017349
## Private household services 0.06052048 0.02017349
## Public administration 0.12104095 0.00000000
## Retail trade 1.45249143 0.06052048
## Social services 0.18156143 0.00000000
## Transportation 0.20173492 0.00000000
## Utilities and sanitary services 0.06052048 0.00000000
## Wholesale trade 0.30260238 0.00000000
## migration_msa
## major_industry_code Nonmover NonMSA to MSA
## Agriculture 1.41214444 0.02017349
## Armed Forces 0.02017349 0.00000000
## Business and repair services 2.03752270 0.02017349
## Communications 0.38329635 0.00000000
## Construction 2.25943111 0.02017349
## Education 3.79261650 0.02017349
## Entertainment 0.72624571 0.00000000
## Finance insurance and real estate 2.80411539 0.00000000
## Forestry and fisheries 0.02017349 0.00000000
## Hospital services 1.63405285 0.00000000
## Manufacturing-durable goods 4.11539237 0.00000000
## Manufacturing-nondurable goods 2.96550333 0.00000000
## Medical except hospital 1.93665524 0.02017349
## Mining 0.22190841 0.00000000
## Not in universe or children 40.22594311 0.22190841
## Other professional services 1.95682873 0.02017349
## Personal services except private HH 1.00867460 0.00000000
## Private household services 0.62537825 0.02017349
## Public administration 2.13839016 0.02017349
## Retail trade 7.20193666 0.06052048
## Social services 1.08936857 0.00000000
## Transportation 1.85596127 0.00000000
## Utilities and sanitary services 0.40346984 0.00000000
## Wholesale trade 1.63405285 0.02017349
## migration_msa
## major_industry_code NonMSA to nonMSA Not identifiable
## Agriculture 0.10086746 0.00000000
## Armed Forces 0.00000000 0.00000000
## Business and repair services 0.04034698 0.00000000
## Communications 0.00000000 0.00000000
## Construction 0.06052048 0.06052048
## Education 0.20173492 0.00000000
## Entertainment 0.02017349 0.00000000
## Finance insurance and real estate 0.14121444 0.00000000
## Forestry and fisheries 0.02017349 0.00000000
## Hospital services 0.06052048 0.02017349
## Manufacturing-durable goods 0.12104095 0.04034698
## Manufacturing-nondurable goods 0.22190841 0.00000000
## Medical except hospital 0.08069397 0.02017349
## Mining 0.00000000 0.02017349
## Not in universe or children 1.25075651 0.06052048
## Other professional services 0.02017349 0.00000000
## Personal services except private HH 0.02017349 0.06052048
## Private household services 0.02017349 0.00000000
## Public administration 0.06052048 0.00000000
## Retail trade 0.40346984 0.12104095
## Social services 0.00000000 0.00000000
## Transportation 0.04034698 0.00000000
## Utilities and sanitary services 0.00000000 0.00000000
## Wholesale trade 0.00000000 0.00000000
## migration_msa
## major_industry_code Not in universe
## Agriculture 0.00000000
## Armed Forces 0.00000000
## Business and repair services 0.00000000
## Communications 0.00000000
## Construction 0.00000000
## Education 0.00000000
## Entertainment 0.00000000
## Finance insurance and real estate 0.00000000
## Forestry and fisheries 0.00000000
## Hospital services 0.00000000
## Manufacturing-durable goods 0.00000000
## Manufacturing-nondurable goods 0.00000000
## Medical except hospital 0.00000000
## Mining 0.00000000
## Not in universe or children 1.75509381
## Other professional services 0.00000000
## Personal services except private HH 0.00000000
## Private household services 0.00000000
## Public administration 0.00000000
## Retail trade 0.00000000
## Social services 0.00000000
## Transportation 0.00000000
## Utilities and sanitary services 0.00000000
## Wholesale trade 0.00000000prop.table(table(major_industry_code,migration_reg))*100## migration_reg
## major_industry_code Abroad
## Agriculture 0.00000000
## Armed Forces 0.00000000
## Business and repair services 0.00000000
## Communications 0.00000000
## Construction 0.04034698
## Education 0.00000000
## Entertainment 0.00000000
## Finance insurance and real estate 0.00000000
## Forestry and fisheries 0.00000000
## Hospital services 0.00000000
## Manufacturing-durable goods 0.04034698
## Manufacturing-nondurable goods 0.02017349
## Medical except hospital 0.00000000
## Mining 0.00000000
## Not in universe or children 0.24208190
## Other professional services 0.02017349
## Personal services except private HH 0.00000000
## Private household services 0.02017349
## Public administration 0.00000000
## Retail trade 0.04034698
## Social services 0.00000000
## Transportation 0.02017349
## Utilities and sanitary services 0.00000000
## Wholesale trade 0.02017349
## migration_reg
## major_industry_code Different county same state
## Agriculture 0.02017349
## Armed Forces 0.00000000
## Business and repair services 0.14121444
## Communications 0.04034698
## Construction 0.18156143
## Education 0.18156143
## Entertainment 0.06052048
## Finance insurance and real estate 0.08069397
## Forestry and fisheries 0.04034698
## Hospital services 0.02017349
## Manufacturing-durable goods 0.18156143
## Manufacturing-nondurable goods 0.06052048
## Medical except hospital 0.10086746
## Mining 0.00000000
## Not in universe or children 0.90780714
## Other professional services 0.02017349
## Personal services except private HH 0.06052048
## Private household services 0.02017349
## Public administration 0.02017349
## Retail trade 0.44381682
## Social services 0.02017349
## Transportation 0.06052048
## Utilities and sanitary services 0.02017349
## Wholesale trade 0.00000000
## migration_reg
## major_industry_code Different division same region
## Agriculture 0.02017349
## Armed Forces 0.00000000
## Business and repair services 0.02017349
## Communications 0.00000000
## Construction 0.00000000
## Education 0.04034698
## Entertainment 0.00000000
## Finance insurance and real estate 0.02017349
## Forestry and fisheries 0.00000000
## Hospital services 0.00000000
## Manufacturing-durable goods 0.00000000
## Manufacturing-nondurable goods 0.04034698
## Medical except hospital 0.02017349
## Mining 0.00000000
## Not in universe or children 0.26225540
## Other professional services 0.02017349
## Personal services except private HH 0.00000000
## Private household services 0.00000000
## Public administration 0.00000000
## Retail trade 0.00000000
## Social services 0.00000000
## Transportation 0.00000000
## Utilities and sanitary services 0.00000000
## Wholesale trade 0.00000000
## migration_reg
## major_industry_code Different region
## Agriculture 0.00000000
## Armed Forces 0.02017349
## Business and repair services 0.04034698
## Communications 0.00000000
## Construction 0.04034698
## Education 0.04034698
## Entertainment 0.00000000
## Finance insurance and real estate 0.02017349
## Forestry and fisheries 0.00000000
## Hospital services 0.00000000
## Manufacturing-durable goods 0.06052048
## Manufacturing-nondurable goods 0.04034698
## Medical except hospital 0.00000000
## Mining 0.00000000
## Not in universe or children 0.58503127
## Other professional services 0.04034698
## Personal services except private HH 0.04034698
## Private household services 0.00000000
## Public administration 0.04034698
## Retail trade 0.20173492
## Social services 0.00000000
## Transportation 0.02017349
## Utilities and sanitary services 0.02017349
## Wholesale trade 0.02017349
## migration_reg
## major_industry_code Different state same division
## Agriculture 0.00000000
## Armed Forces 0.00000000
## Business and repair services 0.04034698
## Communications 0.00000000
## Construction 0.04034698
## Education 0.06052048
## Entertainment 0.00000000
## Finance insurance and real estate 0.02017349
## Forestry and fisheries 0.00000000
## Hospital services 0.00000000
## Manufacturing-durable goods 0.04034698
## Manufacturing-nondurable goods 0.00000000
## Medical except hospital 0.02017349
## Mining 0.02017349
## Not in universe or children 0.34294936
## Other professional services 0.02017349
## Personal services except private HH 0.00000000
## Private household services 0.02017349
## Public administration 0.00000000
## Retail trade 0.10086746
## Social services 0.00000000
## Transportation 0.00000000
## Utilities and sanitary services 0.00000000
## Wholesale trade 0.02017349
## migration_reg
## major_industry_code Nonmover Not in universe
## Agriculture 1.41214444 0.00000000
## Armed Forces 0.02017349 0.00000000
## Business and repair services 2.03752270 0.00000000
## Communications 0.38329635 0.00000000
## Construction 2.25943111 0.00000000
## Education 3.79261650 0.00000000
## Entertainment 0.72624571 0.00000000
## Finance insurance and real estate 2.80411539 0.00000000
## Forestry and fisheries 0.02017349 0.00000000
## Hospital services 1.63405285 0.00000000
## Manufacturing-durable goods 4.11539237 0.00000000
## Manufacturing-nondurable goods 2.96550333 0.00000000
## Medical except hospital 1.93665524 0.00000000
## Mining 0.22190841 0.00000000
## Not in universe or children 40.22594311 1.75509381
## Other professional services 1.95682873 0.00000000
## Personal services except private HH 1.00867460 0.00000000
## Private household services 0.62537825 0.00000000
## Public administration 2.13839016 0.00000000
## Retail trade 7.20193666 0.00000000
## Social services 1.08936857 0.00000000
## Transportation 1.85596127 0.00000000
## Utilities and sanitary services 0.40346984 0.00000000
## Wholesale trade 1.63405285 0.00000000
## migration_reg
## major_industry_code Same county
## Agriculture 0.12104095
## Armed Forces 0.00000000
## Business and repair services 0.24208190
## Communications 0.04034698
## Construction 0.40346984
## Education 0.48416381
## Entertainment 0.08069397
## Finance insurance and real estate 0.36312286
## Forestry and fisheries 0.02017349
## Hospital services 0.22190841
## Manufacturing-durable goods 0.44381682
## Manufacturing-nondurable goods 0.54468428
## Medical except hospital 0.30260238
## Mining 0.02017349
## Not in universe or children 4.31712729
## Other professional services 0.16138794
## Personal services except private HH 0.24208190
## Private household services 0.08069397
## Public administration 0.14121444
## Retail trade 1.35162397
## Social services 0.16138794
## Transportation 0.16138794
## Utilities and sanitary services 0.02017349
## Wholesale trade 0.28242889prop.table(table(major_industry_code,weeks_worked_in_year))*100## weeks_worked_in_year
## major_industry_code 0 1 2 3 4 5
## Agriculture 0.07 0.00 0.00 0.00 0.01 0.00
## Armed Forces 0.00 0.00 0.00 0.00 0.00 0.00
## Business and repair services 0.09 0.04 0.02 0.00 0.01 0.00
## Communications 0.00 0.00 0.00 0.00 0.00 0.00
## Construction 0.11 0.00 0.00 0.01 0.01 0.00
## Education 0.07 0.00 0.01 0.00 0.03 0.00
## Entertainment 0.04 0.02 0.00 0.00 0.00 0.00
## Finance insurance and real estate 0.05 0.00 0.01 0.01 0.00 0.01
## Forestry and fisheries 0.00 0.00 0.00 0.00 0.00 0.00
## Hospital services 0.03 0.00 0.01 0.00 0.00 0.00
## Manufacturing-durable goods 0.12 0.01 0.01 0.00 0.01 0.00
## Manufacturing-nondurable goods 0.11 0.01 0.00 0.00 0.00 0.00
## Medical except hospital 0.09 0.00 0.00 0.00 0.02 0.01
## Mining 0.00 0.00 0.00 0.00 0.00 0.00
## Not in universe or children 44.96 0.22 0.13 0.10 0.26 0.08
## Other professional services 0.05 0.01 0.00 0.01 0.02 0.00
## Personal services except private HH 0.09 0.00 0.00 0.00 0.01 0.00
## Private household services 0.04 0.01 0.00 0.01 0.01 0.00
## Public administration 0.03 0.00 0.03 0.00 0.00 0.00
## Retail trade 0.45 0.00 0.02 0.03 0.09 0.01
## Social services 0.07 0.01 0.01 0.00 0.00 0.00
## Transportation 0.05 0.00 0.00 0.00 0.01 0.01
## Utilities and sanitary services 0.00 0.00 0.00 0.00 0.00 0.00
## Wholesale trade 0.04 0.00 0.01 0.00 0.01 0.00
## weeks_worked_in_year
## major_industry_code 6 7 8 9 10 11
## Agriculture 0.02 0.02 0.03 0.00 0.02 0.00
## Armed Forces 0.00 0.00 0.00 0.00 0.00 0.00
## Business and repair services 0.00 0.00 0.01 0.00 0.02 0.00
## Communications 0.00 0.00 0.00 0.00 0.00 0.00
## Construction 0.00 0.01 0.03 0.01 0.01 0.00
## Education 0.00 0.00 0.02 0.01 0.02 0.01
## Entertainment 0.01 0.02 0.02 0.00 0.00 0.01
## Finance insurance and real estate 0.00 0.00 0.00 0.01 0.01 0.00
## Forestry and fisheries 0.01 0.00 0.00 0.00 0.00 0.00
## Hospital services 0.00 0.00 0.02 0.00 0.00 0.00
## Manufacturing-durable goods 0.02 0.00 0.02 0.02 0.01 0.00
## Manufacturing-nondurable goods 0.01 0.00 0.06 0.00 0.00 0.01
## Medical except hospital 0.00 0.00 0.02 0.00 0.01 0.00
## Mining 0.00 0.00 0.00 0.00 0.00 0.00
## Not in universe or children 0.11 0.03 0.21 0.08 0.14 0.03
## Other professional services 0.00 0.00 0.00 0.00 0.02 0.00
## Personal services except private HH 0.00 0.00 0.02 0.00 0.00 0.00
## Private household services 0.00 0.00 0.00 0.01 0.02 0.00
## Public administration 0.02 0.00 0.01 0.00 0.00 0.00
## Retail trade 0.04 0.00 0.08 0.03 0.01 0.00
## Social services 0.00 0.00 0.00 0.00 0.01 0.00
## Transportation 0.01 0.00 0.00 0.00 0.00 0.00
## Utilities and sanitary services 0.00 0.00 0.00 0.00 0.00 0.00
## Wholesale trade 0.00 0.00 0.02 0.00 0.00 0.00
## weeks_worked_in_year
## major_industry_code 12 13 14 15 16 17
## Agriculture 0.03 0.01 0.00 0.01 0.00 0.01
## Armed Forces 0.00 0.00 0.00 0.00 0.00 0.00
## Business and repair services 0.08 0.01 0.01 0.01 0.05 0.01
## Communications 0.00 0.00 0.00 0.00 0.00 0.00
## Construction 0.01 0.01 0.02 0.00 0.02 0.00
## Education 0.04 0.00 0.00 0.04 0.06 0.00
## Entertainment 0.00 0.01 0.00 0.00 0.01 0.01
## Finance insurance and real estate 0.02 0.00 0.00 0.02 0.02 0.01
## Forestry and fisheries 0.00 0.00 0.00 0.00 0.01 0.00
## Hospital services 0.00 0.01 0.00 0.00 0.00 0.01
## Manufacturing-durable goods 0.05 0.00 0.01 0.00 0.01 0.00
## Manufacturing-nondurable goods 0.01 0.02 0.00 0.01 0.03 0.00
## Medical except hospital 0.00 0.01 0.01 0.00 0.02 0.01
## Mining 0.00 0.00 0.00 0.00 0.00 0.00
## Not in universe or children 0.37 0.09 0.05 0.03 0.13 0.02
## Other professional services 0.01 0.00 0.00 0.00 0.02 0.00
## Personal services except private HH 0.02 0.01 0.00 0.00 0.02 0.00
## Private household services 0.00 0.00 0.00 0.00 0.02 0.00
## Public administration 0.00 0.01 0.00 0.00 0.00 0.01
## Retail trade 0.22 0.04 0.02 0.02 0.04 0.03
## Social services 0.02 0.01 0.00 0.00 0.04 0.00
## Transportation 0.00 0.00 0.00 0.00 0.00 0.01
## Utilities and sanitary services 0.01 0.01 0.00 0.01 0.00 0.00
## Wholesale trade 0.03 0.00 0.00 0.00 0.02 0.01
## weeks_worked_in_year
## major_industry_code 18 19 20 21 22 23
## Agriculture 0.01 0.00 0.01 0.00 0.01 0.00
## Armed Forces 0.00 0.00 0.00 0.00 0.00 0.00
## Business and repair services 0.01 0.00 0.02 0.00 0.00 0.00
## Communications 0.00 0.00 0.01 0.00 0.00 0.01
## Construction 0.01 0.00 0.03 0.01 0.01 0.00
## Education 0.01 0.00 0.05 0.00 0.02 0.01
## Entertainment 0.01 0.00 0.01 0.00 0.00 0.00
## Finance insurance and real estate 0.00 0.01 0.02 0.00 0.01 0.00
## Forestry and fisheries 0.01 0.00 0.00 0.00 0.00 0.00
## Hospital services 0.00 0.00 0.00 0.00 0.00 0.00
## Manufacturing-durable goods 0.00 0.01 0.01 0.01 0.01 0.00
## Manufacturing-nondurable goods 0.00 0.00 0.01 0.01 0.01 0.00
## Medical except hospital 0.00 0.00 0.06 0.00 0.02 0.00
## Mining 0.00 0.00 0.00 0.00 0.00 0.00
## Not in universe or children 0.04 0.00 0.16 0.03 0.06 0.01
## Other professional services 0.00 0.00 0.01 0.00 0.00 0.00
## Personal services except private HH 0.00 0.00 0.02 0.01 0.02 0.00
## Private household services 0.00 0.00 0.00 0.00 0.00 0.00
## Public administration 0.01 0.00 0.01 0.00 0.00 0.00
## Retail trade 0.04 0.01 0.24 0.03 0.02 0.01
## Social services 0.00 0.00 0.03 0.00 0.00 0.00
## Transportation 0.01 0.00 0.01 0.00 0.01 0.00
## Utilities and sanitary services 0.00 0.00 0.00 0.00 0.00 0.00
## Wholesale trade 0.00 0.00 0.00 0.01 0.00 0.00
## weeks_worked_in_year
## major_industry_code 24 25 26 27 28 29
## Agriculture 0.00 0.00 0.02 0.00 0.02 0.00
## Armed Forces 0.00 0.00 0.00 0.00 0.00 0.00
## Business and repair services 0.02 0.00 0.05 0.00 0.04 0.00
## Communications 0.02 0.00 0.01 0.00 0.00 0.00
## Construction 0.02 0.01 0.15 0.00 0.02 0.00
## Education 0.00 0.06 0.03 0.02 0.03 0.01
## Entertainment 0.00 0.00 0.03 0.00 0.00 0.00
## Finance insurance and real estate 0.02 0.00 0.03 0.00 0.01 0.01
## Forestry and fisheries 0.00 0.00 0.00 0.00 0.00 0.00
## Hospital services 0.02 0.00 0.03 0.00 0.00 0.00
## Manufacturing-durable goods 0.04 0.00 0.09 0.00 0.03 0.00
## Manufacturing-nondurable goods 0.03 0.01 0.10 0.00 0.02 0.00
## Medical except hospital 0.00 0.01 0.01 0.00 0.01 0.00
## Mining 0.00 0.00 0.01 0.00 0.00 0.00
## Not in universe or children 0.05 0.03 0.29 0.01 0.04 0.01
## Other professional services 0.00 0.01 0.01 0.00 0.00 0.00
## Personal services except private HH 0.01 0.02 0.03 0.00 0.01 0.00
## Private household services 0.00 0.00 0.00 0.00 0.01 0.00
## Public administration 0.00 0.01 0.03 0.00 0.00 0.00
## Retail trade 0.09 0.03 0.27 0.01 0.07 0.01
## Social services 0.00 0.00 0.03 0.00 0.03 0.00
## Transportation 0.00 0.00 0.03 0.00 0.00 0.00
## Utilities and sanitary services 0.01 0.00 0.00 0.00 0.00 0.00
## Wholesale trade 0.02 0.00 0.01 0.00 0.02 0.00
## weeks_worked_in_year
## major_industry_code 30 32 33 34 35 36
## Agriculture 0.02 0.02 0.00 0.01 0.01 0.00
## Armed Forces 0.00 0.00 0.00 0.00 0.00 0.00
## Business and repair services 0.08 0.01 0.01 0.00 0.01 0.05
## Communications 0.00 0.01 0.00 0.00 0.00 0.00
## Construction 0.07 0.04 0.00 0.00 0.02 0.04
## Education 0.09 0.02 0.00 0.01 0.02 0.17
## Entertainment 0.01 0.01 0.00 0.00 0.01 0.03
## Finance insurance and real estate 0.01 0.01 0.00 0.00 0.01 0.03
## Forestry and fisheries 0.01 0.00 0.00 0.00 0.00 0.00
## Hospital services 0.00 0.00 0.00 0.01 0.00 0.01
## Manufacturing-durable goods 0.01 0.03 0.00 0.00 0.06 0.09
## Manufacturing-nondurable goods 0.01 0.00 0.00 0.01 0.00 0.04
## Medical except hospital 0.03 0.02 0.00 0.00 0.01 0.05
## Mining 0.00 0.00 0.00 0.00 0.00 0.00
## Not in universe or children 0.07 0.06 0.00 0.04 0.03 0.08
## Other professional services 0.01 0.01 0.01 0.00 0.01 0.01
## Personal services except private HH 0.01 0.02 0.00 0.00 0.00 0.01
## Private household services 0.03 0.04 0.00 0.00 0.01 0.01
## Public administration 0.06 0.00 0.00 0.00 0.01 0.02
## Retail trade 0.16 0.08 0.00 0.02 0.06 0.11
## Social services 0.00 0.00 0.00 0.00 0.01 0.04
## Transportation 0.00 0.01 0.00 0.01 0.01 0.01
## Utilities and sanitary services 0.00 0.00 0.00 0.00 0.00 0.00
## Wholesale trade 0.04 0.00 0.00 0.00 0.02 0.01
## weeks_worked_in_year
## major_industry_code 37 38 39 40 41 42
## Agriculture 0.00 0.02 0.00 0.02 0.00 0.00
## Armed Forces 0.00 0.00 0.00 0.01 0.00 0.00
## Business and repair services 0.00 0.02 0.01 0.08 0.01 0.00
## Communications 0.00 0.00 0.00 0.00 0.00 0.00
## Construction 0.00 0.01 0.01 0.10 0.00 0.04
## Education 0.01 0.09 0.03 0.28 0.01 0.09
## Entertainment 0.00 0.00 0.00 0.04 0.00 0.02
## Finance insurance and real estate 0.00 0.00 0.03 0.08 0.00 0.00
## Forestry and fisheries 0.00 0.00 0.00 0.00 0.00 0.00
## Hospital services 0.01 0.00 0.01 0.03 0.00 0.00
## Manufacturing-durable goods 0.02 0.00 0.02 0.09 0.00 0.02
## Manufacturing-nondurable goods 0.01 0.03 0.00 0.05 0.00 0.04
## Medical except hospital 0.00 0.01 0.01 0.07 0.00 0.01
## Mining 0.00 0.00 0.00 0.01 0.00 0.00
## Not in universe or children 0.01 0.02 0.02 0.11 0.00 0.00
## Other professional services 0.00 0.01 0.00 0.08 0.00 0.00
## Personal services except private HH 0.00 0.02 0.00 0.00 0.00 0.00
## Private household services 0.00 0.00 0.00 0.06 0.00 0.00
## Public administration 0.00 0.01 0.00 0.02 0.00 0.00
## Retail trade 0.01 0.05 0.06 0.34 0.00 0.05
## Social services 0.03 0.00 0.00 0.03 0.00 0.00
## Transportation 0.00 0.00 0.00 0.04 0.00 0.03
## Utilities and sanitary services 0.01 0.00 0.00 0.01 0.00 0.00
## Wholesale trade 0.00 0.00 0.02 0.02 0.00 0.00
## weeks_worked_in_year
## major_industry_code 43 44 45 46 47 48
## Agriculture 0.02 0.05 0.00 0.01 0.00 0.02
## Armed Forces 0.00 0.00 0.00 0.00 0.00 0.00
## Business and repair services 0.02 0.01 0.03 0.00 0.00 0.04
## Communications 0.00 0.00 0.01 0.00 0.00 0.01
## Construction 0.01 0.05 0.02 0.04 0.00 0.08
## Education 0.02 0.07 0.05 0.06 0.01 0.11
## Entertainment 0.00 0.00 0.02 0.01 0.00 0.03
## Finance insurance and real estate 0.00 0.00 0.03 0.00 0.00 0.03
## Forestry and fisheries 0.00 0.00 0.00 0.00 0.00 0.00
## Hospital services 0.01 0.02 0.01 0.01 0.01 0.01
## Manufacturing-durable goods 0.04 0.03 0.07 0.04 0.02 0.04
## Manufacturing-nondurable goods 0.02 0.06 0.05 0.01 0.02 0.03
## Medical except hospital 0.00 0.02 0.02 0.01 0.00 0.04
## Mining 0.00 0.00 0.00 0.00 0.00 0.00
## Not in universe or children 0.01 0.00 0.02 0.02 0.00 0.02
## Other professional services 0.00 0.02 0.01 0.00 0.02 0.01
## Personal services except private HH 0.02 0.01 0.03 0.02 0.00 0.03
## Private household services 0.00 0.01 0.01 0.00 0.00 0.00
## Public administration 0.00 0.01 0.00 0.02 0.01 0.01
## Retail trade 0.01 0.05 0.04 0.05 0.02 0.13
## Social services 0.01 0.00 0.01 0.02 0.02 0.01
## Transportation 0.01 0.00 0.01 0.03 0.00 0.06
## Utilities and sanitary services 0.00 0.00 0.00 0.00 0.00 0.01
## Wholesale trade 0.00 0.01 0.01 0.02 0.00 0.04
## weeks_worked_in_year
## major_industry_code 49 50 51 52
## Agriculture 0.00 0.02 0.03 0.99
## Armed Forces 0.00 0.00 0.00 0.01
## Business and repair services 0.02 0.06 0.02 1.70
## Communications 0.00 0.00 0.00 0.47
## Construction 0.03 0.15 0.01 1.85
## Education 0.00 0.07 0.00 2.75
## Entertainment 0.00 0.00 0.01 0.51
## Finance insurance and real estate 0.02 0.05 0.02 2.71
## Forestry and fisheries 0.00 0.00 0.00 0.04
## Hospital services 0.01 0.02 0.01 1.56
## Manufacturing-durable goods 0.04 0.09 0.10 3.21
## Manufacturing-nondurable goods 0.03 0.09 0.05 2.84
## Medical except hospital 0.02 0.06 0.02 1.75
## Mining 0.00 0.00 0.01 0.22
## Not in universe or children 0.00 0.01 0.00 0.69
## Other professional services 0.02 0.05 0.02 1.72
## Personal services except private HH 0.01 0.07 0.02 0.91
## Private household services 0.00 0.00 0.00 0.29
## Public administration 0.00 0.00 0.00 2.01
## Retail trade 0.05 0.18 0.11 5.37
## Social services 0.00 0.07 0.02 0.72
## Transportation 0.02 0.09 0.02 1.68
## Utilities and sanitary services 0.00 0.01 0.00 0.48
## Wholesale trade 0.01 0.05 0.01 1.46prop.table(table(major_industry_code,income_level))*100## income_level
## major_industry_code -50000 50000
## Agriculture 1.43 0.11
## Armed Forces 0.02 0.00
## Business and repair services 2.41 0.27
## Communications 0.45 0.10
## Construction 2.84 0.24
## Education 3.98 0.53
## Entertainment 0.85 0.05
## Finance insurance and real estate 2.77 0.54
## Forestry and fisheries 0.08 0.00
## Hospital services 1.61 0.26
## Manufacturing-durable goods 3.72 0.79
## Manufacturing-nondurable goods 3.41 0.44
## Medical except hospital 2.24 0.22
## Mining 0.21 0.04
## Not in universe or children 48.62 0.36
## Other professional services 1.70 0.48
## Personal services except private HH 1.43 0.04
## Private household services 0.59 0.00
## Public administration 2.04 0.31
## Retail trade 8.53 0.38
## Social services 1.23 0.02
## Transportation 1.89 0.29
## Utilities and sanitary services 0.36 0.20
## Wholesale trade 1.72 0.20prop.table(table(major_industry_code,full_parttime_employment_stat))*100## full_parttime_employment_stat
## major_industry_code Children or Armed Forces
## Agriculture 0.78
## Armed Forces 0.02
## Business and repair services 1.25
## Communications 0.23
## Construction 1.47
## Education 2.28
## Entertainment 0.43
## Finance insurance and real estate 1.64
## Forestry and fisheries 0.04
## Hospital services 0.93
## Manufacturing-durable goods 2.42
## Manufacturing-nondurable goods 1.82
## Medical except hospital 1.18
## Mining 0.13
## Not in universe or children 36.10
## Other professional services 1.11
## Personal services except private HH 0.67
## Private household services 0.38
## Public administration 1.16
## Retail trade 4.63
## Social services 0.63
## Transportation 1.05
## Utilities and sanitary services 0.23
## Wholesale trade 0.98
## full_parttime_employment_stat
## major_industry_code Full-time schedules
## Agriculture 0.54
## Armed Forces 0.00
## Business and repair services 1.12
## Communications 0.29
## Construction 1.18
## Education 1.80
## Entertainment 0.38
## Finance insurance and real estate 1.40
## Forestry and fisheries 0.01
## Hospital services 0.77
## Manufacturing-durable goods 1.83
## Manufacturing-nondurable goods 1.70
## Medical except hospital 1.08
## Mining 0.09
## Not in universe or children 0.00
## Other professional services 0.97
## Personal services except private HH 0.66
## Private household services 0.16
## Public administration 0.96
## Retail trade 3.53
## Social services 0.52
## Transportation 0.88
## Utilities and sanitary services 0.29
## Wholesale trade 0.81
## full_parttime_employment_stat
## major_industry_code Not in labor force
## Agriculture 0.01
## Armed Forces 0.00
## Business and repair services 0.03
## Communications 0.00
## Construction 0.04
## Education 0.01
## Entertainment 0.02
## Finance insurance and real estate 0.03
## Forestry and fisheries 0.02
## Hospital services 0.01
## Manufacturing-durable goods 0.00
## Manufacturing-nondurable goods 0.01
## Medical except hospital 0.02
## Mining 0.00
## Not in universe or children 12.79
## Other professional services 0.01
## Personal services except private HH 0.00
## Private household services 0.02
## Public administration 0.01
## Retail trade 0.07
## Social services 0.00
## Transportation 0.01
## Utilities and sanitary services 0.01
## Wholesale trade 0.02
## full_parttime_employment_stat
## major_industry_code PT for econ reasons usually FT
## Agriculture 0.03
## Armed Forces 0.00
## Business and repair services 0.03
## Communications 0.00
## Construction 0.00
## Education 0.02
## Entertainment 0.00
## Finance insurance and real estate 0.01
## Forestry and fisheries 0.00
## Hospital services 0.00
## Manufacturing-durable goods 0.02
## Manufacturing-nondurable goods 0.00
## Medical except hospital 0.00
## Mining 0.00
## Not in universe or children 0.00
## Other professional services 0.00
## Personal services except private HH 0.02
## Private household services 0.00
## Public administration 0.00
## Retail trade 0.06
## Social services 0.01
## Transportation 0.02
## Utilities and sanitary services 0.00
## Wholesale trade 0.01
## full_parttime_employment_stat
## major_industry_code PT for econ reasons usually PT
## Agriculture 0.08
## Armed Forces 0.00
## Business and repair services 0.07
## Communications 0.00
## Construction 0.11
## Education 0.04
## Entertainment 0.01
## Finance insurance and real estate 0.02
## Forestry and fisheries 0.01
## Hospital services 0.03
## Manufacturing-durable goods 0.03
## Manufacturing-nondurable goods 0.05
## Medical except hospital 0.02
## Mining 0.02
## Not in universe or children 0.00
## Other professional services 0.00
## Personal services except private HH 0.04
## Private household services 0.01
## Public administration 0.06
## Retail trade 0.05
## Social services 0.00
## Transportation 0.06
## Utilities and sanitary services 0.00
## Wholesale trade 0.01
## full_parttime_employment_stat
## major_industry_code PT for non-econ reasons usually FT
## Agriculture 0.04
## Armed Forces 0.00
## Business and repair services 0.09
## Communications 0.03
## Construction 0.16
## Education 0.25
## Entertainment 0.02
## Finance insurance and real estate 0.14
## Forestry and fisheries 0.00
## Hospital services 0.11
## Manufacturing-durable goods 0.08
## Manufacturing-nondurable goods 0.13
## Medical except hospital 0.07
## Mining 0.00
## Not in universe or children 0.00
## Other professional services 0.03
## Personal services except private HH 0.02
## Private household services 0.01
## Public administration 0.14
## Retail trade 0.28
## Social services 0.06
## Transportation 0.11
## Utilities and sanitary services 0.02
## Wholesale trade 0.05
## full_parttime_employment_stat
## major_industry_code Unemployed full-time
## Agriculture 0.06
## Armed Forces 0.00
## Business and repair services 0.08
## Communications 0.00
## Construction 0.11
## Education 0.06
## Entertainment 0.02
## Finance insurance and real estate 0.05
## Forestry and fisheries 0.00
## Hospital services 0.02
## Manufacturing-durable goods 0.13
## Manufacturing-nondurable goods 0.13
## Medical except hospital 0.06
## Mining 0.01
## Not in universe or children 0.05
## Other professional services 0.06
## Personal services except private HH 0.04
## Private household services 0.00
## Public administration 0.01
## Retail trade 0.20
## Social services 0.02
## Transportation 0.04
## Utilities and sanitary services 0.01
## Wholesale trade 0.03
## full_parttime_employment_stat
## major_industry_code Unemployed part- time
## Agriculture 0.00
## Armed Forces 0.00
## Business and repair services 0.01
## Communications 0.00
## Construction 0.01
## Education 0.05
## Entertainment 0.02
## Finance insurance and real estate 0.02
## Forestry and fisheries 0.00
## Hospital services 0.00
## Manufacturing-durable goods 0.00
## Manufacturing-nondurable goods 0.01
## Medical except hospital 0.03
## Mining 0.00
## Not in universe or children 0.04
## Other professional services 0.00
## Personal services except private HH 0.02
## Private household services 0.01
## Public administration 0.01
## Retail trade 0.09
## Social services 0.01
## Transportation 0.01
## Utilities and sanitary services 0.00
## Wholesale trade 0.01prop.table(table(major_industry_code,citizenship))*100## citizenship
## major_industry_code Foreign born- Not a citizen of U S
## Agriculture 0.16
## Armed Forces 0.00
## Business and repair services 0.24
## Communications 0.02
## Construction 0.27
## Education 0.21
## Entertainment 0.09
## Finance insurance and real estate 0.14
## Forestry and fisheries 0.01
## Hospital services 0.13
## Manufacturing-durable goods 0.41
## Manufacturing-nondurable goods 0.42
## Medical except hospital 0.19
## Mining 0.00
## Not in universe or children 2.79
## Other professional services 0.05
## Personal services except private HH 0.24
## Private household services 0.12
## Public administration 0.05
## Retail trade 0.77
## Social services 0.07
## Transportation 0.22
## Utilities and sanitary services 0.03
## Wholesale trade 0.12
## citizenship
## major_industry_code Foreign born- U S citizen by naturalization
## Agriculture 0.03
## Armed Forces 0.00
## Business and repair services 0.05
## Communications 0.03
## Construction 0.10
## Education 0.11
## Entertainment 0.02
## Finance insurance and real estate 0.19
## Forestry and fisheries 0.00
## Hospital services 0.14
## Manufacturing-durable goods 0.26
## Manufacturing-nondurable goods 0.18
## Medical except hospital 0.10
## Mining 0.00
## Not in universe or children 1.05
## Other professional services 0.08
## Personal services except private HH 0.05
## Private household services 0.06
## Public administration 0.07
## Retail trade 0.25
## Social services 0.04
## Transportation 0.09
## Utilities and sanitary services 0.02
## Wholesale trade 0.06
## citizenship
## major_industry_code Native- Born abroad of American Parent(s)
## Agriculture 0.01
## Armed Forces 0.00
## Business and repair services 0.04
## Communications 0.01
## Construction 0.04
## Education 0.04
## Entertainment 0.01
## Finance insurance and real estate 0.06
## Forestry and fisheries 0.00
## Hospital services 0.02
## Manufacturing-durable goods 0.01
## Manufacturing-nondurable goods 0.06
## Medical except hospital 0.01
## Mining 0.00
## Not in universe or children 0.35
## Other professional services 0.02
## Personal services except private HH 0.01
## Private household services 0.00
## Public administration 0.02
## Retail trade 0.12
## Social services 0.00
## Transportation 0.03
## Utilities and sanitary services 0.00
## Wholesale trade 0.02
## citizenship
## major_industry_code Native- Born in Puerto Rico or U S Outlying
## Agriculture 0.00
## Armed Forces 0.00
## Business and repair services 0.02
## Communications 0.00
## Construction 0.02
## Education 0.03
## Entertainment 0.00
## Finance insurance and real estate 0.03
## Forestry and fisheries 0.00
## Hospital services 0.02
## Manufacturing-durable goods 0.04
## Manufacturing-nondurable goods 0.01
## Medical except hospital 0.01
## Mining 0.00
## Not in universe or children 0.36
## Other professional services 0.00
## Personal services except private HH 0.00
## Private household services 0.00
## Public administration 0.00
## Retail trade 0.08
## Social services 0.01
## Transportation 0.01
## Utilities and sanitary services 0.00
## Wholesale trade 0.02
## citizenship
## major_industry_code Native- Born in the United States
## Agriculture 1.34
## Armed Forces 0.02
## Business and repair services 2.33
## Communications 0.49
## Construction 2.65
## Education 4.12
## Entertainment 0.78
## Finance insurance and real estate 2.89
## Forestry and fisheries 0.07
## Hospital services 1.56
## Manufacturing-durable goods 3.79
## Manufacturing-nondurable goods 3.18
## Medical except hospital 2.15
## Mining 0.25
## Not in universe or children 44.43
## Other professional services 2.03
## Personal services except private HH 1.17
## Private household services 0.41
## Public administration 2.21
## Retail trade 7.69
## Social services 1.13
## Transportation 1.83
## Utilities and sanitary services 0.51
## Wholesale trade 1.70prop.table(table(country_self,income_level))*100## income_level
## country_self -50000 50000
## Cambodia 0.06093226 0.00000000
## Canada 0.17264141 0.04062151
## China 0.28435056 0.01015538
## Columbia 0.20310755 0.00000000
## Cuba 0.44683660 0.02031075
## Dominican-Republic 0.38590434 0.01015538
## Ecuador 0.13201990 0.00000000
## El-Salvador 0.33512745 0.00000000
## England 0.24372905 0.06093226
## France 0.05077689 0.00000000
## Germany 0.44683660 0.07108764
## Greece 0.10155377 0.01015538
## Guatemala 0.12186453 0.00000000
## Haiti 0.15233066 0.01015538
## Holand-Netherlands 0.01015538 0.01015538
## Honduras 0.11170915 0.00000000
## Hong Kong 0.05077689 0.00000000
## Hungary 0.04062151 0.02031075
## India 0.16248604 0.01015538
## Iran 0.04062151 0.02031075
## Ireland 0.09139840 0.01015538
## Italy 0.24372905 0.01015538
## Jamaica 0.17264141 0.00000000
## Japan 0.08124302 0.03046613
## Laos 0.04062151 0.00000000
## Mexico 2.74195186 0.08124302
## Nicaragua 0.16248604 0.01015538
## Outlying-U S (Guam USVI etc) 0.04062151 0.00000000
## Panama 0.03046613 0.00000000
## Peru 0.11170915 0.00000000
## Philippines 0.38590434 0.05077689
## Poland 0.30466132 0.01015538
## Portugal 0.07108764 0.01015538
## Puerto-Rico 0.60932264 0.02031075
## Scotland 0.05077689 0.00000000
## South Korea 0.16248604 0.01015538
## Taiwan 0.07108764 0.04062151
## Thailand 0.05077689 0.02031075
## Trinadad&Tobago 0.05077689 0.00000000
## United-States 84.86848786 5.24017467
## Vietnam 0.21326292 0.03046613
## Yugoslavia 0.02031075 0.00000000prop.table(table(citizenship,income_level))*100## income_level
## citizenship -50000 50000
## Foreign born- Not a citizen of U S 6.39 0.36
## Foreign born- U S citizen by naturalization 2.70 0.28
## Native- Born abroad of American Parent(s) 0.83 0.05
## Native- Born in Puerto Rico or U S Outlying 0.64 0.02
## Native- Born in the United States 83.57 5.16prop.table(table(major_industry_code,sex))*100## sex
## major_industry_code Female Male
## Agriculture 0.39 1.15
## Armed Forces 0.00 0.02
## Business and repair services 1.01 1.67
## Communications 0.24 0.31
## Construction 0.34 2.74
## Education 3.16 1.35
## Entertainment 0.46 0.44
## Finance insurance and real estate 2.01 1.30
## Forestry and fisheries 0.00 0.08
## Hospital services 1.43 0.44
## Manufacturing-durable goods 1.25 3.26
## Manufacturing-nondurable goods 1.71 2.14
## Medical except hospital 2.03 0.43
## Mining 0.02 0.23
## Not in universe or children 28.18 20.80
## Other professional services 1.19 0.99
## Personal services except private HH 0.98 0.49
## Private household services 0.53 0.06
## Public administration 1.06 1.29
## Retail trade 4.61 4.30
## Social services 1.05 0.20
## Transportation 0.70 1.48
## Utilities and sanitary services 0.08 0.48
## Wholesale trade 0.69 1.23prop.table(table(marital_status,income_level))*100## income_level
## marital_status -50000 50000
## Divorced 6.02 0.51
## Married-A F spouse present 0.28 0.00
## Married-civilian spouse present 38.11 4.63
## Married-spouse absent 0.78 0.02
## Never married 42.60 0.47
## Separated 1.42 0.06
## Widowed 4.92 0.18prop.table(table(member_of_labor_union,income_level))*100## income_level
## member_of_labor_union -50000 50000
## No 7.77 0.80
## Not in universe 85.05 4.91
## Yes 1.31 0.16prop.table(table(race,sex))*100## sex
## race Female Male
## Amer Indian Aleut or Eskimo 0.66 0.52
## Asian or Pacific Islander 1.63 1.46
## Black 5.80 4.47
## Other 0.96 0.87
## White 44.07 39.56prop.table(table(race,country_self))*100## country_self
## race Cambodia Canada China
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.05077689 0.00000000 0.29450594
## Black 0.00000000 0.01015538 0.00000000
## Other 0.00000000 0.00000000 0.00000000
## White 0.01015538 0.20310755 0.00000000
## country_self
## race Columbia Cuba Dominican-Republic
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.00000000 0.00000000 0.00000000
## Black 0.00000000 0.00000000 0.02031075
## Other 0.00000000 0.02031075 0.09139840
## White 0.20310755 0.44683660 0.28435056
## country_self
## race Ecuador El-Salvador England
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.00000000 0.00000000 0.00000000
## Black 0.00000000 0.01015538 0.00000000
## Other 0.05077689 0.02031075 0.00000000
## White 0.08124302 0.30466132 0.30466132
## country_self
## race France Germany Greece
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.00000000 0.01015538 0.00000000
## Black 0.00000000 0.02031075 0.00000000
## Other 0.00000000 0.01015538 0.00000000
## White 0.05077689 0.47730273 0.11170915
## country_self
## race Guatemala Haiti Holand-Netherlands
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.00000000 0.00000000 0.00000000
## Black 0.00000000 0.16248604 0.00000000
## Other 0.02031075 0.00000000 0.00000000
## White 0.10155377 0.00000000 0.02031075
## country_self
## race Honduras Hong Kong Hungary
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.00000000 0.04062151 0.00000000
## Black 0.00000000 0.00000000 0.00000000
## Other 0.03046613 0.00000000 0.00000000
## White 0.08124302 0.01015538 0.06093226
## country_self
## race India Iran Ireland
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.14217528 0.01015538 0.00000000
## Black 0.00000000 0.00000000 0.00000000
## Other 0.01015538 0.01015538 0.00000000
## White 0.02031075 0.04062151 0.10155377
## country_self
## race Italy Jamaica Japan
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.00000000 0.01015538 0.08124302
## Black 0.01015538 0.14217528 0.00000000
## Other 0.00000000 0.01015538 0.00000000
## White 0.24372905 0.01015538 0.03046613
## country_self
## race Laos Mexico Nicaragua
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.04062151 0.00000000 0.00000000
## Black 0.00000000 0.00000000 0.01015538
## Other 0.00000000 0.43668122 0.00000000
## White 0.00000000 2.38651366 0.16248604
## country_self
## race Outlying-U S (Guam USVI etc) Panama
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000
## Asian or Pacific Islander 0.04062151 0.00000000
## Black 0.00000000 0.00000000
## Other 0.00000000 0.00000000
## White 0.00000000 0.03046613
## country_self
## race Peru Philippines Poland
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.00000000 0.39605971 0.00000000
## Black 0.00000000 0.00000000 0.00000000
## Other 0.02031075 0.00000000 0.00000000
## White 0.09139840 0.04062151 0.31481670
## country_self
## race Portugal Puerto-Rico Scotland
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.00000000 0.01015538 0.00000000
## Black 0.00000000 0.00000000 0.00000000
## Other 0.00000000 0.06093226 0.00000000
## White 0.08124302 0.55854575 0.05077689
## country_self
## race South Korea Taiwan Thailand
## Amer Indian Aleut or Eskimo 0.00000000 0.00000000 0.00000000
## Asian or Pacific Islander 0.17264141 0.11170915 0.07108764
## Black 0.00000000 0.00000000 0.00000000
## Other 0.00000000 0.00000000 0.00000000
## White 0.00000000 0.00000000 0.00000000
## country_self
## race Trinadad&Tobago United-States Vietnam
## Amer Indian Aleut or Eskimo 0.00000000 1.19833452 0.00000000
## Asian or Pacific Islander 0.00000000 1.19833452 0.24372905
## Black 0.03046613 9.79993907 0.00000000
## Other 0.01015538 0.98507160 0.00000000
## White 0.01015538 76.92698284 0.00000000
## country_self
## race Yugoslavia
## Amer Indian Aleut or Eskimo 0.00000000
## Asian or Pacific Islander 0.00000000
## Black 0.00000000
## Other 0.00000000
## White 0.02031075prop.table(table(race,citizenship))*100## citizenship
## race Foreign born- Not a citizen of U S
## Amer Indian Aleut or Eskimo 0.00
## Asian or Pacific Islander 1.20
## Black 0.39
## Other 0.66
## White 4.50
## citizenship
## race Foreign born- U S citizen by naturalization
## Amer Indian Aleut or Eskimo 0.00
## Asian or Pacific Islander 0.58
## Black 0.16
## Other 0.11
## White 2.13
## citizenship
## race Native- Born abroad of American Parent(s)
## Amer Indian Aleut or Eskimo 0.00
## Asian or Pacific Islander 0.08
## Black 0.07
## Other 0.03
## White 0.70
## citizenship
## race Native- Born in Puerto Rico or U S Outlying
## Amer Indian Aleut or Eskimo 0.00
## Asian or Pacific Islander 0.05
## Black 0.00
## Other 0.06
## White 0.55
## citizenship
## race Native- Born in the United States
## Amer Indian Aleut or Eskimo 1.18
## Asian or Pacific Islander 1.18
## Black 9.65
## Other 0.97
## White 75.75prop.table(table(race,citizenship))*100## citizenship
## race Foreign born- Not a citizen of U S
## Amer Indian Aleut or Eskimo 0.00
## Asian or Pacific Islander 1.20
## Black 0.39
## Other 0.66
## White 4.50
## citizenship
## race Foreign born- U S citizen by naturalization
## Amer Indian Aleut or Eskimo 0.00
## Asian or Pacific Islander 0.58
## Black 0.16
## Other 0.11
## White 2.13
## citizenship
## race Native- Born abroad of American Parent(s)
## Amer Indian Aleut or Eskimo 0.00
## Asian or Pacific Islander 0.08
## Black 0.07
## Other 0.03
## White 0.70
## citizenship
## race Native- Born in Puerto Rico or U S Outlying
## Amer Indian Aleut or Eskimo 0.00
## Asian or Pacific Islander 0.05
## Black 0.00
## Other 0.06
## White 0.55
## citizenship
## race Native- Born in the United States
## Amer Indian Aleut or Eskimo 1.18
## Asian or Pacific Islander 1.18
## Black 9.65
## Other 0.97
## White 75.75prop.table(table(race,income_level))*100## income_level
## race -50000 50000
## Amer Indian Aleut or Eskimo 1.13 0.05
## Asian or Pacific Islander 2.86 0.23
## Black 10.02 0.25
## Other 1.78 0.05
## White 78.34 5.29prop.table(table(race,income_level))*100## income_level
## race -50000 50000
## Amer Indian Aleut or Eskimo 1.13 0.05
## Asian or Pacific Islander 2.86 0.23
## Black 10.02 0.25
## Other 1.78 0.05
## White 78.34 5.29prop.table(table(hispanic_origin,income_level))*100## income_level
## hispanic_origin -50000 50000
## All other 81.41237837 5.57728960
## Central or South American 1.93600160 0.02006219
## Chicano 0.12037316 0.00000000
## Cuban 0.59183469 0.02006219
## Do not know 0.16049754 0.00000000
## Mexican-American 3.90209650 0.12037316
## Mexican (Mexicano) 3.58110141 0.05015548
## Other Spanish 1.00310964 0.06018658
## Puerto Rican 1.41438459 0.03009329prop.table(table(race=="White"))*100##
## FALSE TRUE
## 16.37 83.63prop.table(table(sex,income_level))*100## income_level
## sex -50000 50000
## Female 52.00 1.12
## Male 42.13 4.75prop.table(table(sex,tax_filer_status))*100## tax_filer_status
## sex Head of household Joint both 65+ Joint both under 65
## Female 3.10 1.94 17.85
## Male 0.78 2.03 16.93
## tax_filer_status
## sex Joint one under 65 & one 65+ Nonfiler Single
## Female 0.85 20.05 9.33
## Male 0.88 16.71 9.55prop.table(table(member_of_labor_union,citizenship))*100## citizenship
## member_of_labor_union Foreign born- Not a citizen of U S
## No 0.57
## Not in universe 6.11
## Yes 0.07
## citizenship
## member_of_labor_union Foreign born- U S citizen by naturalization
## No 0.28
## Not in universe 2.60
## Yes 0.10
## citizenship
## member_of_labor_union Native- Born abroad of American Parent(s)
## No 0.05
## Not in universe 0.82
## Yes 0.01
## citizenship
## member_of_labor_union Native- Born in Puerto Rico or U S Outlying
## No 0.02
## Not in universe 0.63
## Yes 0.01
## citizenship
## member_of_labor_union Native- Born in the United States
## No 7.65
## Not in universe 79.80
## Yes 1.28