Problem 1
std89c = read.table("~/R_Workspace/data-master/syphilis89c.txt", sep = ",",
header = TRUE)
str(std89c)## 'data.frame': 44081 obs. of 3 variables:
## $ Sex : Factor w/ 2 levels "Female","Male": 2 2 2 2 2 2 2 2 2 2 ...
## $ Race: Factor w/ 3 levels "Black","Other",..: 3 3 3 3 3 3 3 3 3 3 ...
## $ Age : Factor w/ 8 levels "<=14",">55","15-19",..: 1 1 3 3 3 3 3 3 3 3 ...head(std89c)## Sex Race Age
## 1 Male White <=14
## 2 Male White <=14
## 3 Male White 15-19
## 4 Male White 15-19
## 5 Male White 15-19
## 6 Male White 15-19lapply(std89c, table)## $Sex
##
## Female Male
## 18075 26006
##
## $Race
##
## Black Other White
## 35508 3956 4617
##
## $Age
##
## <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## 230 1278 4378 10405 9610 8648 6901 2631table(std89c$Race,std89c$Age,std89c$Sex)## , , = Female
##
##
## <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 165 92 2257 4503 3590 2628 1505 392
## Other 11 15 158 307 283 167 149 40
## White 14 24 253 475 433 316 243 55
##
## , , = Male
##
##
## <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 31 823 1412 4059 4121 4453 3858 1619
## Other 7 108 210 654 633 520 492 202
## White 2 216 88 407 550 564 654 323stdarray<-xtabs(~Race+Age+Sex,data=std89c)
stdarray## , , Sex = Female
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 165 92 2257 4503 3590 2628 1505 392
## Other 11 15 158 307 283 167 149 40
## White 14 24 253 475 433 316 243 55
##
## , , Sex = Male
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 31 823 1412 4059 4121 4453 3858 1619
## Other 7 108 210 654 633 520 492 202
## White 2 216 88 407 550 564 654 323attach(std89c)
table(Race,Age,Sex)## , , Sex = Female
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 165 92 2257 4503 3590 2628 1505 392
## Other 11 15 158 307 283 167 149 40
## White 14 24 253 475 433 316 243 55
##
## , , Sex = Male
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 31 823 1412 4059 4121 4453 3858 1619
## Other 7 108 210 654 633 520 492 202
## White 2 216 88 407 550 564 654 323xtabs(~Race+Age+Sex)## , , Sex = Female
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 165 92 2257 4503 3590 2628 1505 392
## Other 11 15 158 307 283 167 149 40
## White 14 24 253 475 433 316 243 55
##
## , , Sex = Male
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 31 823 1412 4059 4121 4453 3858 1619
## Other 7 108 210 654 633 520 492 202
## White 2 216 88 407 550 564 654 323Problem 2
race_age<-apply(stdarray, c(1, 2), sum)
race_age## Age
## Race <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 196 915 3669 8562 7711 7081 5363 2011
## Other 18 123 368 961 916 687 641 242
## White 16 240 341 882 983 880 897 378sex_age<-apply(stdarray, c(3, 2), sum)
sex_age## Age
## Sex <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Female 190 131 2668 5285 4306 3111 1897 487
## Male 40 1147 1710 5120 5304 5537 5004 2144sex_race<-apply(stdarray, c(3, 1), sum)
sex_race## Race
## Sex Black Other White
## Female 15132 1130 1813
## Male 20376 2826 2804race<-apply(stdarray, 1, sum)
race## Black Other White
## 35508 3956 4617sex<-apply(stdarray, 3, sum)
sex## Female Male
## 18075 26006age<-apply(stdarray, 2, sum)
age## <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## 230 1278 4378 10405 9610 8648 6901 2631Problem 3
row_t <- apply(stdarray, c(1, 3), sum)
row_t## Sex
## Race Female Male
## Black 15132 20376
## Other 1130 2826
## White 1813 2804row_d <- sweep(stdarray, c(1, 3), row_t, "/")
row_d## , , Sex = Female
##
## Age
## Race <=14 >55 15-19 20-24 25-29
## Black 0.0109040444 0.0060798308 0.1491541105 0.2975812847 0.2372455723
## Other 0.0097345133 0.0132743363 0.1398230088 0.2716814159 0.2504424779
## White 0.0077220077 0.0132377275 0.1395477110 0.2619966906 0.2388306674
## Age
## Race 30-34 35-44 45-54
## Black 0.1736716891 0.0994581020 0.0259053661
## Other 0.1477876106 0.1318584071 0.0353982301
## White 0.1742967457 0.1340319912 0.0303364589
##
## , , Sex = Male
##
## Age
## Race <=14 >55 15-19 20-24 25-29
## Black 0.0015213977 0.0403906557 0.0692972124 0.1992049470 0.2022477424
## Other 0.0024769993 0.0382165605 0.0743099788 0.2314225053 0.2239915074
## White 0.0007132668 0.0770328103 0.0313837375 0.1451497860 0.1961483595
## Age
## Race 30-34 35-44 45-54
## Black 0.2185414213 0.1893404005 0.0794562230
## Other 0.1840056617 0.1740976645 0.0714791224
## White 0.2011412268 0.2332382311 0.1151925820apply(row_d, c(1, 3), sum)## Sex
## Race Female Male
## Black 1 1
## Other 1 1
## White 1 1column_t <- apply(stdarray, c(2, 3), sum)
column_t## Sex
## Age Female Male
## <=14 190 40
## >55 131 1147
## 15-19 2668 1710
## 20-24 5285 5120
## 25-29 4306 5304
## 30-34 3111 5537
## 35-44 1897 5004
## 45-54 487 2144column_d <- sweep(stdarray, c(2, 3), column_t, "/")
column_d## , , Sex = Female
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34
## Black 0.86842105 0.70229008 0.84595202 0.85203406 0.83372039 0.84474446
## Other 0.05789474 0.11450382 0.05922039 0.05808893 0.06572225 0.05368049
## White 0.07368421 0.18320611 0.09482759 0.08987701 0.10055736 0.10157506
## Age
## Race 35-44 45-54
## Black 0.79335793 0.80492813
## Other 0.07854507 0.08213552
## White 0.12809700 0.11293634
##
## , , Sex = Male
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34
## Black 0.77500000 0.71752398 0.82573099 0.79277344 0.77696078 0.80422612
## Other 0.17500000 0.09415867 0.12280702 0.12773438 0.11934389 0.09391367
## White 0.05000000 0.18831735 0.05146199 0.07949219 0.10369532 0.10186021
## Age
## Race 35-44 45-54
## Black 0.77098321 0.75513060
## Other 0.09832134 0.09421642
## White 0.13069544 0.15065299apply(column_d, c(2, 3), sum) ## Sex
## Age Female Male
## <=14 1 1
## >55 1 1
## 15-19 1 1
## 20-24 1 1
## 25-29 1 1
## 30-34 1 1
## 35-44 1 1
## 45-54 1 1slice_t <- apply(stdarray, c(1, 2), sum)
slice_t## Age
## Race <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 196 915 3669 8562 7711 7081 5363 2011
## Other 18 123 368 961 916 687 641 242
## White 16 240 341 882 983 880 897 378slice_d <- sweep(stdarray, c(1, 2), slice_t, "/")
slice_d## , , Sex = Female
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34
## Black 0.8418367 0.1005464 0.6151540 0.5259285 0.4655687 0.3711340
## Other 0.6111111 0.1219512 0.4293478 0.3194589 0.3089520 0.2430859
## White 0.8750000 0.1000000 0.7419355 0.5385488 0.4404883 0.3590909
## Age
## Race 35-44 45-54
## Black 0.2806265 0.1949279
## Other 0.2324493 0.1652893
## White 0.2709030 0.1455026
##
## , , Sex = Male
##
## Age
## Race <=14 >55 15-19 20-24 25-29 30-34
## Black 0.1581633 0.8994536 0.3848460 0.4740715 0.5344313 0.6288660
## Other 0.3888889 0.8780488 0.5706522 0.6805411 0.6910480 0.7569141
## White 0.1250000 0.9000000 0.2580645 0.4614512 0.5595117 0.6409091
## Age
## Race 35-44 45-54
## Black 0.7193735 0.8050721
## Other 0.7675507 0.8347107
## White 0.7290970 0.8544974apply(slice_d, c(1, 2), sum)## Age
## Race <=14 >55 15-19 20-24 25-29 30-34 35-44 45-54
## Black 1 1 1 1 1 1 1 1
## Other 1 1 1 1 1 1 1 1
## White 1 1 1 1 1 1 1 1joint_t.race.age <- apply(stdarray, 3, sum)
joint_t.race.age## Female Male
## 18075 26006joint_d.race.age <- sweep(stdarray, 3, joint_t.race.age, "/")
joint_d.race.age## , , Sex = Female
##
## Age
## Race <=14 >55 15-19 20-24 25-29
## Black 9.128631e-03 5.089903e-03 1.248686e-01 2.491286e-01 1.986169e-01
## Other 6.085754e-04 8.298755e-04 8.741355e-03 1.698479e-02 1.565698e-02
## White 7.745505e-04 1.327801e-03 1.399723e-02 2.627939e-02 2.395574e-02
## Age
## Race 30-34 35-44 45-54
## Black 1.453942e-01 8.326418e-02 2.168741e-02
## Other 9.239281e-03 8.243430e-03 2.213001e-03
## White 1.748271e-02 1.344398e-02 3.042877e-03
##
## , , Sex = Male
##
## Age
## Race <=14 >55 15-19 20-24 25-29
## Black 1.192033e-03 3.164654e-02 5.429516e-02 1.560794e-01 1.584634e-01
## Other 2.691687e-04 4.152888e-03 8.075060e-03 2.514804e-02 2.434054e-02
## White 7.690533e-05 8.305776e-03 3.383834e-03 1.565023e-02 2.114897e-02
## Age
## Race 30-34 35-44 45-54
## Black 1.712297e-01 1.483504e-01 6.225486e-02
## Other 1.999539e-02 1.891871e-02 7.767438e-03
## White 2.168730e-02 2.514804e-02 1.242021e-02apply(joint_d.race.age, 3, sum)## Female Male
## 1 1Problem 4
std89b = read.table("~/R_Workspace/data-master/syphilis89b.txt", sep = ",",
header = TRUE)
str(std89b)## 'data.frame': 48 obs. of 4 variables:
## $ Sex : Factor w/ 2 levels "Female","Male": 2 1 2 1 2 1 2 1 2 1 ...
## $ Race: Factor w/ 3 levels "Black","Other",..: 3 3 1 1 2 2 3 3 1 1 ...
## $ Age : Factor w/ 8 levels "<=14",">55","15-19",..: 1 1 1 1 1 1 3 3 3 3 ...
## $ Freq: int 2 14 31 165 7 11 88 253 1412 2257 ...head(std89b)## Sex Race Age Freq
## 1 Male White <=14 2
## 2 Female White <=14 14
## 3 Male Black <=14 31
## 4 Female Black <=14 165
## 5 Male Other <=14 7
## 6 Female Other <=14 11individual.sex<-rep(std89b$Sex,std89b$Freq)
individual.race<-rep(std89b$Race,std89b$Freq)
individual.age<-rep(std89b$Age,std89b$Freq)
individual.data<-data.frame(individual.sex,individual.race,individual.age)
str(individual.data)## 'data.frame': 44081 obs. of 3 variables:
## $ individual.sex : Factor w/ 2 levels "Female","Male": 2 2 1 1 1 1 1 1 1 1 ...
## $ individual.race: Factor w/ 3 levels "Black","Other",..: 3 3 3 3 3 3 3 3 3 3 ...
## $ individual.age : Factor w/ 8 levels "<=14",">55","15-19",..: 1 1 1 1 1 1 1 1 1 1 ...head(individual.data)## individual.sex individual.race individual.age
## 1 Male White <=14
## 2 Male White <=14
## 3 Female White <=14
## 4 Female White <=14
## 5 Female White <=14
## 6 Female White <=14Problem 5
#### 1 Read county names
cty <- scan("~/R_Workspace/data-master/calcounty.txt", what="")Read in the county names.
#### 2 Read county population estimates
calpop = read.csv("~/R_Workspace/data-master/CalCounties2000.txt", header = T)Read in the population estimates.
#### 2 Replace county number with county name
for(i in 1:length(cty)){
calpop$County[calpop$County==i] <- cty[i]
}Replaced the numbers withe the actual county names.
#### 3 Discretize age into categories
calpop$Agecat <- cut(calpop$Age, c(0,20,45,65,100),
include.lowest = TRUE, right = FALSE) Created age categories.
#### 4 Create combined API category
calpop$AsianPI <- calpop$Asian + calpop$Pac.IslCreated combined Asian & Pacific Islander column.
#### 5 Shorten selected ethnic labels
names(calpop)[c(6, 9, 10)] = c("Latino", "AfrAmer", "AmerInd")Created shorter ethnicity labels.
#### 6 Index Bay Area Counties
baindex <- calpop$County=="Alameda" | calpop$County=="San Francisco"
bapop <- calpop[baindex,]
bapop## County Year Sex Age White Latino Asian Pac.Islander AfrAmer
## 1 Alameda 2000 F 0 2751 2910 1921 63 1346
## 2 Alameda 2000 F 1 2673 2837 1820 70 1343
## 3 Alameda 2000 F 2 2654 2770 1930 64 1442
## 4 Alameda 2000 F 3 2646 2798 1998 64 1455
## 5 Alameda 2000 F 4 2780 2762 2029 85 1558
## 6 Alameda 2000 F 5 2826 2738 1998 93 1632
## 7 Alameda 2000 F 6 2871 2872 1984 78 1657
## 8 Alameda 2000 F 7 2942 2837 1993 94 1732
## 9 Alameda 2000 F 8 3087 2756 1957 85 1817
## 10 Alameda 2000 F 9 3070 2603 2031 83 1819
## 11 Alameda 2000 F 10 3076 2465 1967 89 1820
## 12 Alameda 2000 F 11 3056 2315 1945 77 1802
## 13 Alameda 2000 F 12 3167 2236 1897 71 1762
## 14 Alameda 2000 F 13 3077 2168 1862 78 1570
## 15 Alameda 2000 F 14 2979 2094 1736 82 1573
## 16 Alameda 2000 F 15 3027 2023 1855 93 1524
## 17 Alameda 2000 F 16 2972 1987 1869 79 1543
## 18 Alameda 2000 F 17 2880 2045 1896 69 1552
## 19 Alameda 2000 F 18 2787 2210 2056 93 1442
## 20 Alameda 2000 F 19 2839 2312 2307 92 1376
## 21 Alameda 2000 F 20 2870 2371 2522 86 1469
## 22 Alameda 2000 F 21 2869 2417 2526 92 1462
## 23 Alameda 2000 F 22 3079 2581 2399 86 1445
## 24 Alameda 2000 F 23 3260 2629 2432 83 1490
## 25 Alameda 2000 F 24 3430 2675 2573 77 1540
## 26 Alameda 2000 F 25 3694 2771 2731 73 1597
## 27 Alameda 2000 F 26 3701 2748 2790 74 1636
## 28 Alameda 2000 F 27 3874 2861 2966 88 1696
## 29 Alameda 2000 F 28 4037 2837 3022 76 1773
## 30 Alameda 2000 F 29 4449 2734 3125 87 1915
## 31 Alameda 2000 F 30 4978 2680 3324 86 2097
## 32 Alameda 2000 F 31 4792 2540 3251 85 1847
## 33 Alameda 2000 F 32 4521 2493 3062 101 1667
## 34 Alameda 2000 F 33 4462 2383 2887 82 1719
## 35 Alameda 2000 F 34 4612 2341 2916 73 1877
## 36 Alameda 2000 F 35 5100 2362 3077 90 2110
## 37 Alameda 2000 F 36 5252 2295 3195 92 2030
## 38 Alameda 2000 F 37 5183 2172 3145 91 1909
## 39 Alameda 2000 F 38 5330 2154 2923 90 1922
## 40 Alameda 2000 F 39 5484 1961 2815 95 1924
## 41 Alameda 2000 F 40 5586 1934 2847 99 2044
## 42 Alameda 2000 F 41 5453 1790 2645 92 1872
## 43 Alameda 2000 F 42 5460 1697 2607 83 1885
## 44 Alameda 2000 F 43 5456 1569 2538 70 1754
## 45 Alameda 2000 F 44 5394 1558 2484 70 1757
## 46 Alameda 2000 F 45 5445 1532 2485 62 1835
## 47 Alameda 2000 F 46 5328 1423 2337 68 1676
## 48 Alameda 2000 F 47 5310 1306 2266 64 1765
## 49 Alameda 2000 F 48 5204 1197 2190 51 1679
## 50 Alameda 2000 F 49 5179 1181 2174 54 1629
## 51 Alameda 2000 F 50 5274 1179 2246 69 1728
## 52 Alameda 2000 F 51 5099 1126 2085 58 1597
## 53 Alameda 2000 F 52 5206 1089 1870 43 1508
## 54 Alameda 2000 F 53 5387 1001 1721 36 1433
## 55 Alameda 2000 F 54 4387 884 1479 35 1186
## 56 Alameda 2000 F 55 4132 841 1363 30 1164
## 57 Alameda 2000 F 56 3921 759 1284 28 1059
## 58 Alameda 2000 F 57 3776 755 1202 25 987
## 59 Alameda 2000 F 58 3308 668 1166 20 973
## 60 Alameda 2000 F 59 2915 659 1144 25 918
## 61 Alameda 2000 F 60 2775 694 1103 29 884
## 62 Alameda 2000 F 61 2658 603 1065 25 783
## 63 Alameda 2000 F 62 2464 573 1082 26 751
## 64 Alameda 2000 F 63 2274 558 1099 24 725
## 65 Alameda 2000 F 64 2163 506 1079 24 668
## 66 Alameda 2000 F 65 2219 505 1106 24 735
## 67 Alameda 2000 F 66 2075 445 1065 26 650
## 68 Alameda 2000 F 67 2016 462 986 18 637
## 69 Alameda 2000 F 68 1994 468 958 21 577
## 70 Alameda 2000 F 69 1984 459 949 15 589
## 71 Alameda 2000 F 70 2154 465 943 12 648
## 72 Alameda 2000 F 71 2074 396 888 13 593
## 73 Alameda 2000 F 72 2046 392 841 18 588
## 74 Alameda 2000 F 73 2160 397 815 15 613
## 75 Alameda 2000 F 74 2307 368 824 12 638
## 76 Alameda 2000 F 75 2301 336 767 11 628
## 77 Alameda 2000 F 76 2272 317 715 13 585
## 78 Alameda 2000 F 77 2209 302 615 8 541
## 79 Alameda 2000 F 78 2246 276 539 4 521
## 80 Alameda 2000 F 79 2127 248 533 5 490
## 81 Alameda 2000 F 80 1980 216 455 6 501
## 82 Alameda 2000 F 81 1800 201 393 7 441
## 83 Alameda 2000 F 82 1679 178 347 9 414
## 84 Alameda 2000 F 83 1542 158 307 4 358
## 85 Alameda 2000 F 84 1445 143 281 3 300
## 86 Alameda 2000 F 85 1355 127 262 2 303
## 87 Alameda 2000 F 86 1294 108 234 2 263
## 88 Alameda 2000 F 87 1113 110 188 3 213
## 89 Alameda 2000 F 88 990 98 145 2 182
## 90 Alameda 2000 F 89 861 68 130 2 149
## 91 Alameda 2000 F 90 717 65 102 3 121
## 92 Alameda 2000 F 91 580 52 78 2 102
## 93 Alameda 2000 F 92 503 39 56 1 91
## 94 Alameda 2000 F 93 438 43 46 0 76
## 95 Alameda 2000 F 94 360 24 36 0 56
## 96 Alameda 2000 F 95 254 21 34 0 50
## 97 Alameda 2000 F 96 208 12 24 0 46
## 98 Alameda 2000 F 97 146 13 18 0 39
## 99 Alameda 2000 F 98 88 15 21 0 25
## 100 Alameda 2000 F 99 87 10 14 1 22
## 101 Alameda 2000 F 100 138 11 27 0 49
## 102 Alameda 2000 M 0 2905 3025 2033 57 1344
## 103 Alameda 2000 M 1 2788 2983 1985 76 1346
## 104 Alameda 2000 M 2 2793 2913 2007 82 1452
## 105 Alameda 2000 M 3 2841 2896 2132 77 1539
## 106 Alameda 2000 M 4 2914 2877 2141 75 1620
## 107 Alameda 2000 M 5 3082 2971 2178 95 1632
## 108 Alameda 2000 M 6 3068 2904 2214 87 1720
## 109 Alameda 2000 M 7 3113 2934 2128 82 1785
## 110 Alameda 2000 M 8 3228 2801 2177 88 1800
## 111 Alameda 2000 M 9 3282 2748 2108 81 1874
## 112 Alameda 2000 M 10 3287 2669 2052 76 1968
## 113 Alameda 2000 M 11 3214 2445 2110 89 1825
## 114 Alameda 2000 M 12 3212 2398 2002 90 1706
## 115 Alameda 2000 M 13 3174 2223 1876 86 1603
## 116 Alameda 2000 M 14 3211 2168 1882 95 1561
## 117 Alameda 2000 M 15 3120 2194 1963 79 1568
## 118 Alameda 2000 M 16 3044 2244 1970 89 1553
## 119 Alameda 2000 M 17 3125 2365 1947 76 1557
## 120 Alameda 2000 M 18 3014 2559 2038 84 1488
## 121 Alameda 2000 M 19 3031 2780 2322 93 1336
## 122 Alameda 2000 M 20 3163 3058 2539 91 1347
## 123 Alameda 2000 M 21 3075 3086 2454 84 1278
## 124 Alameda 2000 M 22 3179 3161 2233 81 1178
## 125 Alameda 2000 M 23 3261 3120 2266 70 1216
## 126 Alameda 2000 M 24 3458 3257 2297 73 1271
## 127 Alameda 2000 M 25 3752 3349 2494 70 1312
## 128 Alameda 2000 M 26 3715 3352 2566 75 1256
## 129 Alameda 2000 M 27 3910 3374 2811 82 1317
## 130 Alameda 2000 M 28 4100 3351 2897 74 1340
## 131 Alameda 2000 M 29 4555 3481 2988 82 1491
## 132 Alameda 2000 M 30 5165 3412 3078 84 1731
## 133 Alameda 2000 M 31 4873 3032 2995 85 1579
## 134 Alameda 2000 M 32 4627 2944 2827 75 1441
## 135 Alameda 2000 M 33 4641 2817 2701 78 1452
## 136 Alameda 2000 M 34 4823 2802 2749 84 1558
## 137 Alameda 2000 M 35 5355 2815 3011 86 1762
## 138 Alameda 2000 M 36 5464 2561 3048 104 1624
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## 145 Alameda 2000 M 43 5492 1777 2412 69 1464
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## 149 Alameda 2000 M 47 5327 1276 2044 56 1403
## 150 Alameda 2000 M 48 5207 1235 1993 55 1300
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## 152 Alameda 2000 M 50 5217 1163 2032 56 1453
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## 155 Alameda 2000 M 53 5282 914 1525 49 1146
## 156 Alameda 2000 M 54 4377 799 1346 40 975
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## 159 Alameda 2000 M 57 3892 657 1054 30 866
## 160 Alameda 2000 M 58 3334 625 949 21 770
## 161 Alameda 2000 M 59 2890 558 980 25 751
## 162 Alameda 2000 M 60 2754 554 1023 23 754
## 163 Alameda 2000 M 61 2573 521 926 26 697
## 164 Alameda 2000 M 62 2403 457 904 25 606
## 165 Alameda 2000 M 63 2152 457 863 15 615
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## 167 Alameda 2000 M 65 1985 426 854 22 588
## 168 Alameda 2000 M 66 1851 385 829 18 499
## 169 Alameda 2000 M 67 1813 366 782 17 490
## 170 Alameda 2000 M 68 1786 362 754 20 471
## 171 Alameda 2000 M 69 1735 361 751 15 460
## 172 Alameda 2000 M 70 1749 333 733 12 432
## 173 Alameda 2000 M 71 1672 333 672 17 390
## 174 Alameda 2000 M 72 1648 311 634 10 405
## 175 Alameda 2000 M 73 1655 278 619 7 411
## 176 Alameda 2000 M 74 1618 252 561 4 435
## 177 Alameda 2000 M 75 1599 268 578 8 388
## 178 Alameda 2000 M 76 1577 254 528 7 346
## 179 Alameda 2000 M 77 1498 200 476 4 344
## 180 Alameda 2000 M 78 1526 191 408 3 346
## 181 Alameda 2000 M 79 1384 194 361 3 314
## 182 Alameda 2000 M 80 1256 147 368 3 312
## 183 Alameda 2000 M 81 1118 118 274 2 227
## 184 Alameda 2000 M 82 1002 98 232 2 209
## 185 Alameda 2000 M 83 884 82 218 5 162
## 186 Alameda 2000 M 84 810 75 174 3 161
## 187 Alameda 2000 M 85 777 62 139 4 142
## 188 Alameda 2000 M 86 659 58 138 2 108
## 189 Alameda 2000 M 87 513 54 119 1 87
## 190 Alameda 2000 M 88 411 52 105 1 77
## 191 Alameda 2000 M 89 342 36 88 2 67
## 192 Alameda 2000 M 90 280 29 64 1 49
## 193 Alameda 2000 M 91 231 29 43 0 33
## 194 Alameda 2000 M 92 165 23 48 0 20
## 195 Alameda 2000 M 93 125 10 36 1 20
## 196 Alameda 2000 M 94 107 10 22 0 24
## 197 Alameda 2000 M 95 73 7 13 0 17
## 198 Alameda 2000 M 96 49 3 10 1 14
## 199 Alameda 2000 M 97 32 3 10 0 12
## 200 Alameda 2000 M 98 20 3 7 0 9
## 201 Alameda 2000 M 99 17 2 4 0 6
## 202 Alameda 2000 M 100 27 1 8 0 12
## 7475 San Francisco 2000 F 0 1248 782 949 26 279
## 7476 San Francisco 2000 F 1 1012 693 936 22 285
## 7477 San Francisco 2000 F 2 784 667 936 22 266
## 7478 San Francisco 2000 F 3 731 694 950 29 283
## 7479 San Francisco 2000 F 4 660 656 982 35 307
## 7480 San Francisco 2000 F 5 622 669 1097 30 320
## 7481 San Francisco 2000 F 6 582 659 1102 35 380
## 7482 San Francisco 2000 F 7 602 675 1148 25 387
## 7483 San Francisco 2000 F 8 616 677 1168 22 395
## 7484 San Francisco 2000 F 9 608 671 1152 38 386
## 7485 San Francisco 2000 F 10 651 654 1133 36 398
## 7486 San Francisco 2000 F 11 639 592 1205 31 361
## 7487 San Francisco 2000 F 12 623 616 1184 25 391
## 7488 San Francisco 2000 F 13 651 612 1130 26 358
## 7489 San Francisco 2000 F 14 626 572 1148 33 348
## 7490 San Francisco 2000 F 15 633 588 1213 28 368
## 7491 San Francisco 2000 F 16 621 600 1260 30 353
## 7492 San Francisco 2000 F 17 617 631 1297 37 367
## 7493 San Francisco 2000 F 18 822 738 1254 42 370
## 7494 San Francisco 2000 F 19 1007 805 1404 45 384
## 7495 San Francisco 2000 F 20 1157 857 1573 39 361
## 7496 San Francisco 2000 F 21 1336 865 1619 40 350
## 7497 San Francisco 2000 F 22 2114 943 1779 40 342
## 7498 San Francisco 2000 F 23 3278 1032 2006 31 380
## 7499 San Francisco 2000 F 24 3993 1125 2195 31 379
## 7500 San Francisco 2000 F 25 4590 1202 2323 40 376
## 7501 San Francisco 2000 F 26 4747 1185 2394 40 362
## 7502 San Francisco 2000 F 27 4872 1170 2458 41 357
## 7503 San Francisco 2000 F 28 5259 1166 2418 37 409
## 7504 San Francisco 2000 F 29 5721 1198 2415 39 430
## 7505 San Francisco 2000 F 30 6054 1230 2448 42 484
## 7506 San Francisco 2000 F 31 5140 1067 2223 40 422
## 7507 San Francisco 2000 F 32 4370 1017 2071 41 392
## 7508 San Francisco 2000 F 33 3934 930 1951 30 376
## 7509 San Francisco 2000 F 34 3622 890 1973 35 394
## 7510 San Francisco 2000 F 35 3577 891 2100 34 428
## 7511 San Francisco 2000 F 36 3136 858 2107 31 422
## 7512 San Francisco 2000 F 37 2739 782 2113 33 441
## 7513 San Francisco 2000 F 38 2560 758 1962 26 444
## 7514 San Francisco 2000 F 39 2457 711 1877 32 429
## 7515 San Francisco 2000 F 40 2524 748 1973 32 489
## 7516 San Francisco 2000 F 41 2230 761 1901 31 440
## 7517 San Francisco 2000 F 42 2112 713 1909 20 486
## 7518 San Francisco 2000 F 43 2123 676 1908 19 456
## 7519 San Francisco 2000 F 44 2121 683 1943 16 435
## 7520 San Francisco 2000 F 45 2219 709 1971 23 485
## 7521 San Francisco 2000 F 46 2111 619 1893 17 459
## 7522 San Francisco 2000 F 47 2223 589 1874 15 433
## 7523 San Francisco 2000 F 48 2222 553 1866 18 405
## 7524 San Francisco 2000 F 49 2188 528 1924 19 388
## 7525 San Francisco 2000 F 50 2327 574 2206 25 407
## 7526 San Francisco 2000 F 51 2212 530 2091 15 392
## 7527 San Francisco 2000 F 52 2284 472 1800 17 396
## 7528 San Francisco 2000 F 53 2341 441 1600 20 357
## 7529 San Francisco 2000 F 54 1914 441 1408 19 313
## 7530 San Francisco 2000 F 55 1793 420 1322 14 291
## 7531 San Francisco 2000 F 56 1695 381 1187 11 319
## 7532 San Francisco 2000 F 57 1619 379 1127 10 316
## 7533 San Francisco 2000 F 58 1413 385 1183 13 273
## 7534 San Francisco 2000 F 59 1277 365 1220 15 283
## 7535 San Francisco 2000 F 60 1265 373 1305 10 317
## 7536 San Francisco 2000 F 61 1213 368 1249 11 261
## 7537 San Francisco 2000 F 62 1164 353 1320 11 263
## 7538 San Francisco 2000 F 63 1098 356 1293 15 259
## 7539 San Francisco 2000 F 64 1039 348 1329 12 273
## 7540 San Francisco 2000 F 65 979 348 1325 10 259
## 7541 San Francisco 2000 F 66 932 339 1362 4 234
## 7542 San Francisco 2000 F 67 937 309 1289 5 245
## 7543 San Francisco 2000 F 68 958 298 1213 9 224
## 7544 San Francisco 2000 F 69 1016 335 1317 9 231
## 7545 San Francisco 2000 F 70 1087 320 1396 10 232
## 7546 San Francisco 2000 F 71 1081 303 1278 8 231
## 7547 San Francisco 2000 F 72 1129 281 1260 8 243
## 7548 San Francisco 2000 F 73 1138 254 1277 8 254
## 7549 San Francisco 2000 F 74 1208 260 1262 5 237
## 7550 San Francisco 2000 F 75 1257 245 1135 3 258
## 7551 San Francisco 2000 F 76 1261 223 996 4 249
## 7552 San Francisco 2000 F 77 1265 242 913 6 240
## 7553 San Francisco 2000 F 78 1198 232 855 3 239
## 7554 San Francisco 2000 F 79 1168 193 773 3 199
## 7555 San Francisco 2000 F 80 1091 211 718 2 196
## 7556 San Francisco 2000 F 81 995 156 628 2 171
## 7557 San Francisco 2000 F 82 925 145 540 5 159
## 7558 San Francisco 2000 F 83 882 139 487 3 157
## 7559 San Francisco 2000 F 84 839 126 454 3 156
## 7560 San Francisco 2000 F 85 870 137 395 3 136
## 7561 San Francisco 2000 F 86 815 120 343 1 119
## 7562 San Francisco 2000 F 87 748 118 305 1 88
## 7563 San Francisco 2000 F 88 644 85 271 2 77
## 7564 San Francisco 2000 F 89 548 65 221 3 69
## 7565 San Francisco 2000 F 90 475 58 177 1 50
## 7566 San Francisco 2000 F 91 408 48 153 2 48
## 7567 San Francisco 2000 F 92 310 39 122 4 44
## 7568 San Francisco 2000 F 93 278 36 105 1 34
## 7569 San Francisco 2000 F 94 215 31 85 0 25
## 7570 San Francisco 2000 F 95 151 23 65 0 22
## 7571 San Francisco 2000 F 96 106 14 52 0 9
## 7572 San Francisco 2000 F 97 86 10 45 0 8
## 7573 San Francisco 2000 F 98 67 9 31 0 6
## 7574 San Francisco 2000 F 99 50 10 20 0 7
## 7575 San Francisco 2000 F 100 98 11 47 1 16
## 7576 San Francisco 2000 M 0 1245 850 981 29 269
## 7577 San Francisco 2000 M 1 1043 749 921 27 279
## 7578 San Francisco 2000 M 2 876 723 941 24 314
## 7579 San Francisco 2000 M 3 790 721 1054 31 327
## 7580 San Francisco 2000 M 4 732 696 1080 31 335
## 7581 San Francisco 2000 M 5 708 713 1141 35 336
## 7582 San Francisco 2000 M 6 683 732 1147 38 332
## 7583 San Francisco 2000 M 7 627 713 1123 40 330
## 7584 San Francisco 2000 M 8 661 688 1172 34 389
## 7585 San Francisco 2000 M 9 633 696 1211 29 382
## 7586 San Francisco 2000 M 10 669 692 1263 39 409
## 7587 San Francisco 2000 M 11 671 644 1276 41 383
## 7588 San Francisco 2000 M 12 648 651 1263 37 356
## 7589 San Francisco 2000 M 13 616 591 1245 29 385
## 7590 San Francisco 2000 M 14 654 585 1270 33 388
## 7591 San Francisco 2000 M 15 653 624 1303 34 342
## 7592 San Francisco 2000 M 16 653 670 1343 45 346
## 7593 San Francisco 2000 M 17 686 778 1365 37 360
## 7594 San Francisco 2000 M 18 765 902 1357 32 346
## 7595 San Francisco 2000 M 19 868 1062 1411 29 351
## 7596 San Francisco 2000 M 20 1076 1190 1546 26 348
## 7597 San Francisco 2000 M 21 1247 1189 1529 21 328
## 7598 San Francisco 2000 M 22 1749 1308 1653 25 302
## 7599 San Francisco 2000 M 23 2783 1351 1829 41 322
## 7600 San Francisco 2000 M 24 3630 1378 2020 35 342
## 7601 San Francisco 2000 M 25 4593 1575 2155 39 351
## 7602 San Francisco 2000 M 26 4913 1529 2190 28 345
## 7603 San Francisco 2000 M 27 5117 1554 2251 25 351
## 7604 San Francisco 2000 M 28 5729 1602 2252 31 403
## 7605 San Francisco 2000 M 29 6456 1613 2210 32 428
## 7606 San Francisco 2000 M 30 7205 1767 2294 38 501
## 7607 San Francisco 2000 M 31 6476 1533 2102 29 483
## 7608 San Francisco 2000 M 32 5829 1412 1879 31 446
## 7609 San Francisco 2000 M 33 5315 1285 1763 31 439
## 7610 San Francisco 2000 M 34 5116 1369 1810 30 443
## 7611 San Francisco 2000 M 35 5331 1332 1940 37 539
## 7612 San Francisco 2000 M 36 4780 1244 1877 35 499
## 7613 San Francisco 2000 M 37 4246 1056 1934 36 500
## 7614 San Francisco 2000 M 38 4045 994 1813 38 502
## 7615 San Francisco 2000 M 39 3703 990 1762 36 535
## 7616 San Francisco 2000 M 40 3803 1005 1850 41 586
## 7617 San Francisco 2000 M 41 3307 914 1740 26 549
## 7618 San Francisco 2000 M 42 3229 858 1732 25 570
## 7619 San Francisco 2000 M 43 3156 825 1734 24 522
## 7620 San Francisco 2000 M 44 2964 732 1737 17 477
## 7621 San Francisco 2000 M 45 3117 756 1814 19 522
## 7622 San Francisco 2000 M 46 2914 689 1696 18 495
## 7623 San Francisco 2000 M 47 2830 657 1643 19 474
## 7624 San Francisco 2000 M 48 2846 617 1546 18 495
## 7625 San Francisco 2000 M 49 2840 603 1639 15 486
## 7626 San Francisco 2000 M 50 2974 590 1916 22 536
## 7627 San Francisco 2000 M 51 2702 490 1811 14 474
## 7628 San Francisco 2000 M 52 2697 481 1569 14 415
## 7629 San Francisco 2000 M 53 2732 450 1328 13 391
## 7630 San Francisco 2000 M 54 2334 402 1118 10 315
## 7631 San Francisco 2000 M 55 2199 370 1109 6 323
## 7632 San Francisco 2000 M 56 1999 353 1007 10 294
## 7633 San Francisco 2000 M 57 1849 316 937 15 311
## 7634 San Francisco 2000 M 58 1608 286 972 9 257
## 7635 San Francisco 2000 M 59 1496 307 957 10 268
## 7636 San Francisco 2000 M 60 1478 302 1046 10 293
## 7637 San Francisco 2000 M 61 1392 275 1023 6 262
## 7638 San Francisco 2000 M 62 1325 260 998 3 257
## 7639 San Francisco 2000 M 63 1234 230 997 9 253
## 7640 San Francisco 2000 M 64 1128 240 1027 11 231
## 7641 San Francisco 2000 M 65 1133 256 1104 10 242
## 7642 San Francisco 2000 M 66 1035 237 1139 10 209
## 7643 San Francisco 2000 M 67 988 205 1077 10 205
## 7644 San Francisco 2000 M 68 967 196 975 4 175
## 7645 San Francisco 2000 M 69 1044 226 1005 7 178
## 7646 San Francisco 2000 M 70 1086 228 1038 8 192
## 7647 San Francisco 2000 M 71 1015 207 955 10 167
## 7648 San Francisco 2000 M 72 992 194 913 9 182
## 7649 San Francisco 2000 M 73 972 182 900 6 180
## 7650 San Francisco 2000 M 74 935 177 876 6 163
## 7651 San Francisco 2000 M 75 1000 164 912 6 137
## 7652 San Francisco 2000 M 76 962 149 810 5 140
## 7653 San Francisco 2000 M 77 836 133 821 5 138
## 7654 San Francisco 2000 M 78 825 124 736 3 138
## 7655 San Francisco 2000 M 79 794 99 579 3 127
## 7656 San Francisco 2000 M 80 741 96 538 1 130
## 7657 San Francisco 2000 M 81 648 81 418 2 111
## 7658 San Francisco 2000 M 82 578 83 335 3 96
## 7659 San Francisco 2000 M 83 524 45 305 3 64
## 7660 San Francisco 2000 M 84 518 45 295 1 53
## 7661 San Francisco 2000 M 85 462 50 248 1 45
## 7662 San Francisco 2000 M 86 387 48 203 2 42
## 7663 San Francisco 2000 M 87 346 35 166 3 39
## 7664 San Francisco 2000 M 88 293 30 148 1 40
## 7665 San Francisco 2000 M 89 238 30 141 0 32
## 7666 San Francisco 2000 M 90 187 29 110 0 15
## 7667 San Francisco 2000 M 91 145 15 87 0 15
## 7668 San Francisco 2000 M 92 117 15 70 0 16
## 7669 San Francisco 2000 M 93 86 10 45 0 16
## 7670 San Francisco 2000 M 94 60 8 40 1 12
## 7671 San Francisco 2000 M 95 49 7 23 0 9
## 7672 San Francisco 2000 M 96 31 9 11 0 9
## 7673 San Francisco 2000 M 97 22 5 12 1 3
## 7674 San Francisco 2000 M 98 13 2 8 1 0
## 7675 San Francisco 2000 M 99 15 0 8 0 2
## 7676 San Francisco 2000 M 100 28 8 17 0 7
## AmerInd Multirace Agecat AsianPI
## 1 32 711 [0,20) 1984
## 2 37 574 [0,20) 1890
## 3 37 579 [0,20) 1994
## 4 39 588 [0,20) 2062
## 5 38 575 [0,20) 2114
## 6 45 576 [0,20) 2091
## 7 53 548 [0,20) 2062
## 8 51 514 [0,20) 2087
## 9 43 545 [0,20) 2042
## 10 44 537 [0,20) 2114
## 11 39 524 [0,20) 2056
## 12 40 489 [0,20) 2022
## 13 47 475 [0,20) 1968
## 14 40 463 [0,20) 1940
## 15 37 433 [0,20) 1818
## 16 47 431 [0,20) 1948
## 17 51 402 [0,20) 1948
## 18 33 384 [0,20) 1965
## 19 45 388 [0,20) 2149
## 20 41 384 [0,20) 2399
## 21 49 361 [20,45) 2608
## 22 51 357 [20,45) 2618
## 23 45 350 [20,45) 2485
## 24 50 356 [20,45) 2515
## 25 42 356 [20,45) 2650
## 26 48 328 [20,45) 2804
## 27 48 318 [20,45) 2864
## 28 48 318 [20,45) 3054
## 29 64 320 [20,45) 3098
## 30 66 333 [20,45) 3212
## 31 59 338 [20,45) 3410
## 32 51 308 [20,45) 3336
## 33 49 293 [20,45) 3163
## 34 47 281 [20,45) 2969
## 35 60 280 [20,45) 2989
## 36 67 313 [20,45) 3167
## 37 75 288 [20,45) 3287
## 38 71 272 [20,45) 3236
## 39 54 277 [20,45) 3013
## 40 61 295 [20,45) 2910
## 41 68 285 [20,45) 2946
## 42 60 273 [20,45) 2737
## 43 51 265 [20,45) 2690
## 44 54 254 [20,45) 2608
## 45 63 239 [20,45) 2554
## 46 60 233 [45,65) 2547
## 47 59 219 [45,65) 2405
## 48 55 227 [45,65) 2330
## 49 60 199 [45,65) 2241
## 50 55 182 [45,65) 2228
## 51 46 199 [45,65) 2315
## 52 64 178 [45,65) 2143
## 53 53 172 [45,65) 1913
## 54 52 166 [45,65) 1757
## 55 46 146 [45,65) 1514
## 56 40 133 [45,65) 1393
## 57 34 127 [45,65) 1312
## 58 26 124 [45,65) 1227
## 59 30 106 [45,65) 1186
## 60 36 91 [45,65) 1169
## 61 32 96 [45,65) 1132
## 62 22 86 [45,65) 1090
## 63 15 87 [45,65) 1108
## 64 19 79 [45,65) 1123
## 65 18 72 [45,65) 1103
## 66 14 71 [65,100] 1130
## 67 9 69 [65,100] 1091
## 68 17 65 [65,100] 1004
## 69 15 62 [65,100] 979
## 70 12 62 [65,100] 964
## 71 10 63 [65,100] 955
## 72 11 54 [65,100] 901
## 73 12 49 [65,100] 859
## 74 13 48 [65,100] 830
## 75 12 51 [65,100] 836
## 76 13 43 [65,100] 778
## 77 15 40 [65,100] 728
## 78 10 42 [65,100] 623
## 79 9 41 [65,100] 543
## 80 7 48 [65,100] 538
## 81 9 42 [65,100] 461
## 82 5 28 [65,100] 400
## 83 5 23 [65,100] 356
## 84 6 17 [65,100] 311
## 85 8 16 [65,100] 284
## 86 7 12 [65,100] 264
## 87 5 13 [65,100] 236
## 88 8 9 [65,100] 191
## 89 5 9 [65,100] 147
## 90 3 7 [65,100] 132
## 91 2 8 [65,100] 105
## 92 2 4 [65,100] 80
## 93 0 3 [65,100] 57
## 94 1 3 [65,100] 46
## 95 1 3 [65,100] 36
## 96 0 3 [65,100] 34
## 97 0 2 [65,100] 24
## 98 0 1 [65,100] 18
## 99 0 1 [65,100] 21
## 100 0 1 [65,100] 15
## 101 0 1 [65,100] 27
## 102 30 755 [0,20) 2090
## 103 37 606 [0,20) 2061
## 104 30 602 [0,20) 2089
## 105 36 585 [0,20) 2209
## 106 32 576 [0,20) 2216
## 107 44 596 [0,20) 2273
## 108 38 550 [0,20) 2301
## 109 44 532 [0,20) 2210
## 110 55 528 [0,20) 2265
## 111 48 550 [0,20) 2189
## 112 48 524 [0,20) 2128
## 113 45 478 [0,20) 2199
## 114 49 470 [0,20) 2092
## 115 47 453 [0,20) 1962
## 116 40 453 [0,20) 1977
## 117 40 387 [0,20) 2042
## 118 34 379 [0,20) 2059
## 119 50 362 [0,20) 2023
## 120 42 364 [0,20) 2122
## 121 39 352 [0,20) 2415
## 122 37 312 [20,45) 2630
## 123 49 305 [20,45) 2538
## 124 53 292 [20,45) 2314
## 125 49 257 [20,45) 2336
## 126 36 284 [20,45) 2370
## 127 38 301 [20,45) 2564
## 128 39 297 [20,45) 2641
## 129 47 286 [20,45) 2893
## 130 42 293 [20,45) 2971
## 131 43 309 [20,45) 3070
## 132 56 308 [20,45) 3162
## 133 59 283 [20,45) 3080
## 134 70 257 [20,45) 2902
## 135 41 256 [20,45) 2779
## 136 46 267 [20,45) 2833
## 137 74 271 [20,45) 3097
## 138 58 262 [20,45) 3152
## 139 48 253 [20,45) 3096
## 140 48 253 [20,45) 2812
## 141 65 257 [20,45) 2695
## 142 55 279 [20,45) 2877
## 143 57 238 [20,45) 2742
## 144 56 243 [20,45) 2593
## 145 53 225 [20,45) 2481
## 146 44 207 [20,45) 2425
## 147 53 220 [45,65) 2453
## 148 46 204 [45,65) 2289
## 149 49 174 [45,65) 2100
## 150 47 164 [45,65) 2048
## 151 44 159 [45,65) 1987
## 152 38 162 [45,65) 2088
## 153 39 151 [45,65) 1929
## 154 42 147 [45,65) 1797
## 155 52 147 [45,65) 1574
## 156 37 120 [45,65) 1386
## 157 28 126 [45,65) 1292
## 158 38 113 [45,65) 1195
## 159 27 101 [45,65) 1084
## 160 32 98 [45,65) 970
## 161 32 77 [45,65) 1005
## 162 24 83 [45,65) 1046
## 163 19 72 [45,65) 952
## 164 18 64 [45,65) 929
## 165 11 66 [45,65) 878
## 166 11 58 [45,65) 839
## 167 14 51 [65,100] 876
## 168 12 49 [65,100] 847
## 169 4 53 [65,100] 799
## 170 5 46 [65,100] 774
## 171 7 45 [65,100] 766
## 172 7 35 [65,100] 745
## 173 9 39 [65,100] 689
## 174 10 34 [65,100] 644
## 175 11 35 [65,100] 626
## 176 7 35 [65,100] 565
## 177 7 32 [65,100] 586
## 178 8 25 [65,100] 535
## 179 9 26 [65,100] 480
## 180 5 29 [65,100] 411
## 181 7 30 [65,100] 364
## 182 5 28 [65,100] 371
## 183 3 24 [65,100] 276
## 184 4 15 [65,100] 234
## 185 3 8 [65,100] 223
## 186 2 11 [65,100] 177
## 187 3 10 [65,100] 143
## 188 2 10 [65,100] 140
## 189 2 7 [65,100] 120
## 190 0 5 [65,100] 106
## 191 3 6 [65,100] 90
## 192 3 6 [65,100] 65
## 193 2 3 [65,100] 43
## 194 1 3 [65,100] 48
## 195 0 3 [65,100] 37
## 196 0 2 [65,100] 22
## 197 0 1 [65,100] 13
## 198 1 2 [65,100] 11
## 199 0 2 [65,100] 10
## 200 0 0 [65,100] 7
## 201 0 0 [65,100] 4
## 202 0 1 [65,100] 8
## 7475 9 267 [0,20) 975
## 7476 8 202 [0,20) 958
## 7477 9 174 [0,20) 958
## 7478 11 183 [0,20) 979
## 7479 7 156 [0,20) 1017
## 7480 8 143 [0,20) 1127
## 7481 9 132 [0,20) 1137
## 7482 6 145 [0,20) 1173
## 7483 12 153 [0,20) 1190
## 7484 6 139 [0,20) 1190
## 7485 7 131 [0,20) 1169
## 7486 8 124 [0,20) 1236
## 7487 11 132 [0,20) 1209
## 7488 11 126 [0,20) 1156
## 7489 5 124 [0,20) 1181
## 7490 5 127 [0,20) 1241
## 7491 6 115 [0,20) 1290
## 7492 9 119 [0,20) 1334
## 7493 12 122 [0,20) 1296
## 7494 14 126 [0,20) 1449
## 7495 14 117 [20,45) 1612
## 7496 15 114 [20,45) 1659
## 7497 17 139 [20,45) 1819
## 7498 16 177 [20,45) 2037
## 7499 22 181 [20,45) 2226
## 7500 20 199 [20,45) 2363
## 7501 24 204 [20,45) 2434
## 7502 20 202 [20,45) 2499
## 7503 26 212 [20,45) 2455
## 7504 28 221 [20,45) 2454
## 7505 24 208 [20,45) 2490
## 7506 25 179 [20,45) 2263
## 7507 25 163 [20,45) 2112
## 7508 20 147 [20,45) 1981
## 7509 20 136 [20,45) 2008
## 7510 18 146 [20,45) 2134
## 7511 18 134 [20,45) 2138
## 7512 23 117 [20,45) 2146
## 7513 18 103 [20,45) 1988
## 7514 23 95 [20,45) 1909
## 7515 26 104 [20,45) 2005
## 7516 29 94 [20,45) 1932
## 7517 18 95 [20,45) 1929
## 7518 19 87 [20,45) 1927
## 7519 18 82 [20,45) 1959
## 7520 22 83 [45,65) 1994
## 7521 21 78 [45,65) 1910
## 7522 14 78 [45,65) 1889
## 7523 12 76 [45,65) 1884
## 7524 18 66 [45,65) 1943
## 7525 20 79 [45,65) 2231
## 7526 21 74 [45,65) 2106
## 7527 21 69 [45,65) 1817
## 7528 17 66 [45,65) 1620
## 7529 16 58 [45,65) 1427
## 7530 17 55 [45,65) 1336
## 7531 9 55 [45,65) 1198
## 7532 10 47 [45,65) 1137
## 7533 9 35 [45,65) 1196
## 7534 8 35 [45,65) 1235
## 7535 9 41 [45,65) 1315
## 7536 6 38 [45,65) 1260
## 7537 8 34 [45,65) 1331
## 7538 12 40 [45,65) 1308
## 7539 12 37 [45,65) 1341
## 7540 6 35 [65,100] 1335
## 7541 6 26 [65,100] 1366
## 7542 6 23 [65,100] 1294
## 7543 7 28 [65,100] 1222
## 7544 7 26 [65,100] 1326
## 7545 4 26 [65,100] 1406
## 7546 5 27 [65,100] 1286
## 7547 9 33 [65,100] 1268
## 7548 5 29 [65,100] 1285
## 7549 4 28 [65,100] 1267
## 7550 4 33 [65,100] 1138
## 7551 4 25 [65,100] 1000
## 7552 8 23 [65,100] 919
## 7553 5 24 [65,100] 858
## 7554 3 14 [65,100] 776
## 7555 2 17 [65,100] 720
## 7556 2 18 [65,100] 630
## 7557 2 17 [65,100] 545
## 7558 3 12 [65,100] 490
## 7559 4 11 [65,100] 457
## 7560 4 11 [65,100] 398
## 7561 4 13 [65,100] 344
## 7562 6 11 [65,100] 306
## 7563 4 9 [65,100] 273
## 7564 1 5 [65,100] 224
## 7565 1 4 [65,100] 178
## 7566 1 5 [65,100] 155
## 7567 1 5 [65,100] 126
## 7568 2 5 [65,100] 106
## 7569 0 3 [65,100] 85
## 7570 1 3 [65,100] 65
## 7571 0 2 [65,100] 52
## 7572 0 1 [65,100] 45
## 7573 0 1 [65,100] 31
## 7574 0 0 [65,100] 20
## 7575 0 1 [65,100] 48
## 7576 12 278 [0,20) 1010
## 7577 8 213 [0,20) 948
## 7578 4 187 [0,20) 965
## 7579 7 182 [0,20) 1085
## 7580 8 159 [0,20) 1111
## 7581 8 133 [0,20) 1176
## 7582 9 134 [0,20) 1185
## 7583 11 138 [0,20) 1163
## 7584 8 132 [0,20) 1206
## 7585 10 126 [0,20) 1240
## 7586 9 129 [0,20) 1302
## 7587 8 133 [0,20) 1317
## 7588 8 121 [0,20) 1300
## 7589 8 109 [0,20) 1274
## 7590 5 119 [0,20) 1303
## 7591 7 123 [0,20) 1337
## 7592 7 108 [0,20) 1388
## 7593 7 105 [0,20) 1402
## 7594 10 110 [0,20) 1389
## 7595 11 112 [0,20) 1440
## 7596 16 105 [20,45) 1572
## 7597 19 103 [20,45) 1550
## 7598 19 131 [20,45) 1678
## 7599 21 145 [20,45) 1870
## 7600 23 162 [20,45) 2055
## 7601 30 171 [20,45) 2194
## 7602 37 172 [20,45) 2218
## 7603 34 186 [20,45) 2276
## 7604 36 196 [20,45) 2283
## 7605 38 198 [20,45) 2242
## 7606 37 213 [20,45) 2332
## 7607 39 199 [20,45) 2131
## 7608 35 170 [20,45) 1910
## 7609 33 154 [20,45) 1794
## 7610 38 144 [20,45) 1840
## 7611 40 160 [20,45) 1977
## 7612 35 165 [20,45) 1912
## 7613 34 141 [20,45) 1970
## 7614 35 126 [20,45) 1851
## 7615 35 132 [20,45) 1798
## 7616 37 140 [20,45) 1891
## 7617 32 125 [20,45) 1766
## 7618 22 119 [20,45) 1757
## 7619 33 111 [20,45) 1758
## 7620 24 98 [20,45) 1754
## 7621 24 106 [45,65) 1833
## 7622 28 101 [45,65) 1714
## 7623 21 96 [45,65) 1662
## 7624 27 80 [45,65) 1564
## 7625 21 84 [45,65) 1654
## 7626 25 100 [45,65) 1938
## 7627 19 78 [45,65) 1825
## 7628 20 62 [45,65) 1583
## 7629 24 65 [45,65) 1341
## 7630 17 57 [45,65) 1128
## 7631 13 51 [45,65) 1115
## 7632 17 43 [45,65) 1017
## 7633 16 42 [45,65) 952
## 7634 19 43 [45,65) 981
## 7635 11 38 [45,65) 967
## 7636 16 40 [45,65) 1056
## 7637 13 32 [45,65) 1029
## 7638 8 33 [45,65) 1001
## 7639 10 35 [45,65) 1006
## 7640 5 34 [45,65) 1038
## 7641 8 29 [65,100] 1114
## 7642 5 19 [65,100] 1149
## 7643 5 23 [65,100] 1087
## 7644 6 20 [65,100] 979
## 7645 5 22 [65,100] 1012
## 7646 6 30 [65,100] 1046
## 7647 3 24 [65,100] 965
## 7648 2 28 [65,100] 922
## 7649 4 29 [65,100] 906
## 7650 4 23 [65,100] 882
## 7651 2 20 [65,100] 918
## 7652 1 20 [65,100] 815
## 7653 2 17 [65,100] 826
## 7654 2 18 [65,100] 739
## 7655 1 16 [65,100] 582
## 7656 2 15 [65,100] 539
## 7657 3 15 [65,100] 420
## 7658 2 12 [65,100] 338
## 7659 1 10 [65,100] 308
## 7660 2 9 [65,100] 296
## 7661 1 9 [65,100] 249
## 7662 2 7 [65,100] 205
## 7663 1 9 [65,100] 169
## 7664 1 5 [65,100] 149
## 7665 2 4 [65,100] 141
## 7666 2 3 [65,100] 110
## 7667 0 2 [65,100] 87
## 7668 0 2 [65,100] 70
## 7669 0 3 [65,100] 45
## 7670 1 3 [65,100] 41
## 7671 0 2 [65,100] 23
## 7672 0 1 [65,100] 11
## 7673 0 0 [65,100] 13
## 7674 0 0 [65,100] 9
## 7675 0 0 [65,100] 8
## 7676 0 1 [65,100] 17Pulled out just San Francisco and Alameda county.
#### 7 Labels for later use
agelabs <- names(table(bapop$Agecat))
sexlabs <- c("Female", "Male")
racen <- c("White", "AfrAmer", "AsianPI", "Latino", "Multirace",
"AmerInd")
ctylabs <- names(table(bapop$County))Created labels.
#### 8 Aggregate
bapop2 <- aggregate(bapop[,racen], list(Agecat = bapop$Agecat,
Sex = bapop$Sex, County = bapop$County), sum)
bapop2## Agecat Sex County White AfrAmer AsianPI Latino Multirace
## 1 [0,20) F Alameda 58160 31765 40653 49738 10120
## 2 [20,45) F Alameda 112326 44437 72923 58553 7658
## 3 [45,65) F Alameda 82205 24948 33236 18534 2922
## 4 [65,100] F Alameda 49762 12834 16004 7548 1014
## 5 [0,20) M Alameda 61446 32277 42922 53097 10102
## 6 [20,45) M Alameda 115745 36976 69053 69233 6795
## 7 [45,65) M Alameda 81332 20737 29841 17402 2506
## 8 [65,100] M Alameda 33994 8087 11855 5416 711
## 9 [0,20) F San Francisco 14355 6986 23265 13251 2940
## 10 [20,45) F San Francisco 85766 10284 52479 23458 3656
## 11 [45,65) F San Francisco 35617 6890 31478 9184 1144
## 12 [65,100] F San Francisco 27215 5172 23044 5773 554
## 13 [0,20) M San Francisco 14881 6959 24541 14480 2851
## 14 [20,45) M San Francisco 105798 11111 48379 31605 3766
## 15 [45,65) M San Francisco 43694 7352 26404 8674 1220
## 16 [65,100] M San Francisco 20072 3329 17190 3428 450
## AmerInd
## 1 839
## 2 1401
## 3 822
## 4 246
## 5 828
## 6 1263
## 7 687
## 8 156
## 9 173
## 10 526
## 11 282
## 12 121
## 13 165
## 14 782
## 15 354
## 16 76Aggregated by age category.
#### 9 Temp matrix of counts
tmp <- as.matrix(cbind(bapop2[1:4,racen], bapop2[5:8,racen],
bapop2[9:12,racen], bapop2[13:16,racen]))Counts by race.
#### 10 Convert into final array
bapop3 <- array(tmp, c(4, 6, 2, 2))
dimnames(bapop3) <- list(agelabs, racen, sexlabs, ctylabs)
bapop3## , , Female, Alameda
##
## White AfrAmer AsianPI Latino Multirace AmerInd
## [0,20) 58160 31765 40653 49738 10120 839
## [20,45) 112326 44437 72923 58553 7658 1401
## [45,65) 82205 24948 33236 18534 2922 822
## [65,100] 49762 12834 16004 7548 1014 246
##
## , , Male, Alameda
##
## White AfrAmer AsianPI Latino Multirace AmerInd
## [0,20) 61446 32277 42922 53097 10102 828
## [20,45) 115745 36976 69053 69233 6795 1263
## [45,65) 81332 20737 29841 17402 2506 687
## [65,100] 33994 8087 11855 5416 711 156
##
## , , Female, San Francisco
##
## White AfrAmer AsianPI Latino Multirace AmerInd
## [0,20) 14355 6986 23265 13251 2940 173
## [20,45) 85766 10284 52479 23458 3656 526
## [45,65) 35617 6890 31478 9184 1144 282
## [65,100] 27215 5172 23044 5773 554 121
##
## , , Male, San Francisco
##
## White AfrAmer AsianPI Latino Multirace AmerInd
## [0,20) 14881 6959 24541 14480 2851 165
## [20,45) 105798 11111 48379 31605 3766 782
## [45,65) 43694 7352 26404 8674 1220 354
## [65,100] 20072 3329 17190 3428 450 76