If you are using the package for the first time, you will have to first install it
# install.packages("survival")
library(survival)## Warning: package 'survival' was built under R version 4.0.4Load data sets from package
pbc <- survival::pbc
pbcseq <- survival::pbcseqObtain the mean of columns time and age in the pbc data set
apply(pbc[, c(2,5)], 2, mean)## time age
## 1917.78230 50.74155apply(pbc[, c("time", "age")], 2, mean)## time age
## 1917.78230 50.74155Obtain the mean of rows in the pbc data set
Before running the code, think if it is meaningful
# apply(pbc[, ], 1, mean)Obtain the standardized values of columns time, age and bili in the pbc data set
apply(pbc[, c("time", "age", "bili")], 2, function(x) { (x-mean(x))/sd(x) } )## time age bili
## [1,] -1.373965243 0.768020788 2.559085710
## [2,] 2.337540359 0.546051607 -0.481182150
## [3,] -0.819955139 1.850349850 -0.413116451
## [4,] 0.006533792 0.382785020 -0.322362187
## [5,] -0.374574466 -1.209522821 0.040654871
## [6,] 0.529765557 1.485293099 -0.549247848
## [7,] -0.077654018 0.458783913 -0.503870716
## [8,] 0.496271482 0.221614954 -0.662690679
## [9,] 0.436525295 -0.788122063 -0.004722261
## [10,] -1.689895842 1.896997447 2.128002953
## [11,] 1.669469351 0.284510589 -0.413116451
## [12,] -1.460868789 0.803661648 0.086032003
## [13,] 1.501998976 -0.483602360 -0.571936414
## [14,] -0.634379859 0.524562265 -0.549247848
## [15,] 1.508335693 1.330936726 -0.549247848
## [16,] 1.587997277 -0.985719184 -0.571936414
## [17,] -1.039929739 0.138016171 -0.118165092
## [18,] -1.617476221 0.305213736 1.855740160
## [19,] 2.094934627 -0.113042241 -0.571936414
## [20,] -0.508550766 0.881757062 0.426360495
## [21,] 1.382506600 1.287171847 -0.594624980
## [22,] -1.126833285 0.529803568 0.040654871
## [23,] -1.497078600 0.500190206 3.217054127
## [24,] 1.956432101 -0.595504179 -0.254296489
## [25,] 1.999883874 -0.542567019 -0.571936414
## [26,] -0.428889183 0.122816393 0.449049061
## [27,] -1.666359465 0.353957854 4.169973904
## [28,] -1.239083698 -0.554622015 3.171676995
## [29,] 2.345687567 1.257296420 -0.571936414
## [30,] -1.445479619 -0.895568773 0.086032003
## [31,] 1.739173236 -0.879582799 0.335606230
## [32,] 2.358361000 0.311503300 -0.322362187
## [33,] 1.133564152 0.051796738 -0.549247848
## [34,] 1.824266292 0.126223240 -0.549247848
## [35,] 0.841169930 -0.203192652 -0.458493584
## [36,] 1.532777315 0.542644760 -0.662690679
## [37,] -1.534193656 1.051575278 0.880131817
## [38,] 1.200552301 -1.351038001 0.017966305
## [39,] 0.343285032 0.445156525 -0.571936414
## [40,] 2.307667265 -0.389783037 -0.435805018
## [41,] -0.513982238 -1.637475208 0.812066119
## [42,] 2.294993831 -1.631709775 -0.254296489
## [43,] 2.388234094 -0.179082658 -0.481182150
## [44,] 1.367117431 -1.259577264 0.017966305
## [45,] 1.907548856 -0.856521066 -0.594624980
## [46,] 0.306169976 -0.473119754 0.562491892
## [47,] 0.595848462 -0.317190991 -0.617313546
## [48,] 2.271457454 -0.153662339 -0.299673621
## [49,] -1.095149700 0.996541597 -0.549247848
## [50,] 0.615763858 0.264855703 -0.481182150
## [51,] 1.751846670 0.128843891 -0.549247848
## [52,] 0.423851861 -0.019222917 0.630557590
## [53,] -0.830818082 1.595360461 -0.140853658
## [54,] -0.437941635 -1.104958827 -0.435805018
## [55,] -0.504929785 1.437859307 -0.322362187
## [56,] -0.064075339 -1.639047599 -0.481182150
## [57,] 1.234951622 0.270883202 -0.208919356
## [58,] 2.300425303 -0.590787006 -0.571936414
## [59,] 0.277202127 -0.990436357 -0.549247848
## [60,] 2.215332248 0.731331667 -0.526559282
## [61,] 2.116660514 -0.654992967 -0.594624980
## [62,] 1.061144530 0.953824978 -0.435805018
## [63,] -0.958457665 -0.393714014 4.374170999
## [64,] -0.389963636 1.164525357 -0.254296489
## [65,] 1.877675763 -1.008780917 -0.458493584
## [66,] 2.057819571 -0.410486184 -0.413116451
## [67,] 0.770560799 0.052320868 -0.481182150
## [68,] 1.920222290 -1.735225508 -0.571936414
## [69,] -0.676926386 -0.134269518 3.806956846
## [70,] 1.394274789 0.541596500 -0.594624980
## [71,] 2.062345797 -0.181441244 -0.458493584
## [72,] 2.051482854 -1.746756375 -0.617313546
## [73,] 2.056914326 -1.172309570 -0.571936414
## [74,] -0.082180245 0.112857917 1.175083177
## [75,] -0.657916236 -0.691420023 3.148988429
## [76,] -1.671790937 0.114954438 2.037248689
## [77,] -1.440953393 -0.087621921 0.766688987
## [78,] -0.206198846 -0.267660678 0.698623288
## [79,] 1.619680861 -0.404458685 -0.549247848
## [80,] -0.930395061 1.595622526 0.902820383
## [81,] 0.563259632 1.198593827 2.536397144
## [82,] 1.499283240 1.585926116 0.290229098
## [83,] 1.930179988 0.504645314 -0.435805018
## [84,] 1.913885573 0.487086949 -0.640002113
## [85,] 1.303750262 -0.337370007 -0.254296489
## [86,] -0.236071940 0.193049853 0.403671929
## [87,] -1.556824788 -1.288666496 -0.481182150
## [88,] 0.483598048 -0.894782578 -0.594624980
## [89,] -0.160031338 0.162912361 -0.276985055
## [90,] 0.698141177 -1.652674987 -0.367739319
## [91,] -1.319650527 -0.491464315 0.403671929
## [92,] -1.384828186 2.485595770 -0.413116451
## [93,] 1.806161386 -1.359948216 -0.435805018
## [94,] -1.057129399 0.303903410 -0.004722261
## [95,] -1.618381466 -0.416513682 3.217054127
## [96,] 1.749130934 -0.181441244 -0.503870716
## [97,] -1.182958491 2.024623174 -0.276985055
## [98,] 1.724689312 -2.092158240 -0.503870716
## [99,] 1.721973576 -0.217606235 -0.322362187
## [100,] -1.236367962 0.069617168 -0.208919356
## [101,] 1.505619957 -0.554359950 -0.526559282
## [102,] 1.069291737 0.557844539 -0.526559282
## [103,] -1.636486371 -0.170172443 -0.163542224
## [104,] 1.057523549 -0.739377945 -0.481182150
## [105,] 1.062955021 -1.598689566 -0.481182150
## [106,] 1.180636906 1.700710651 -0.254296489
## [107,] 1.330907620 1.127574171 -0.594624980
## [108,] 0.602185179 -0.036781282 -0.640002113
## [109,] 0.530670802 -0.639269058 -0.617313546
## [110,] 0.169477940 -1.132475667 -0.299673621
## [111,] 0.391263031 -0.917844311 0.517114759
## [112,] 1.382506600 0.451446089 -0.276985055
## [113,] -0.848922987 0.047079565 0.789377553
## [114,] 1.337244337 0.199601481 -0.004722261
## [115,] 1.361685959 -0.775542935 -0.571936414
## [116,] 1.283834866 0.988679643 -0.050099394
## [117,] -0.755682725 -0.103869960 0.744000420
## [118,] 0.335137824 -0.180655049 0.063343437
## [119,] -1.269862037 0.336399489 -0.594624980
## [120,] 0.104300281 -1.492291116 0.063343437
## [121,] -1.563161504 1.643056318 -0.435805018
## [122,] 1.248530301 0.449349568 -0.594624980
## [123,] -0.857070195 -0.471023233 0.426360495
## [124,] 1.042134379 0.205628980 -0.594624980
## [125,] 0.498081973 -0.340776854 -0.435805018
## [126,] -0.990141249 0.273503853 -0.458493584
## [127,] 1.210509999 -0.635338081 -0.617313546
## [128,] -0.797324007 -0.841583353 2.944791334
## [129,] 1.196026075 1.232138166 -0.526559282
## [130,] -0.456951786 -0.623545149 3.217054127
## [131,] -0.966604872 1.077781793 -0.095476526
## [132,] 0.928978721 -0.975236578 -0.299673621
## [133,] 0.795002421 1.139367103 -0.390427885
## [134,] 1.114554001 -0.804632167 -0.571936414
## [135,] 1.115459246 -0.744095118 -0.640002113
## [136,] 1.068386492 0.499666076 -0.549247848
## [137,] 0.970620003 1.160070250 -0.481182150
## [138,] -0.561960237 0.048651956 0.925508949
## [139,] 0.170383185 -0.380872822 -0.481182150
## [140,] 1.033081927 0.319103189 -0.481182150
## [141,] 1.024934719 -0.354666307 -0.526559282
## [142,] 0.453724955 0.477128473 -0.503870716
## [143,] -1.024540569 -0.444030523 -0.072787960
## [144,] -0.882417062 0.147974647 5.622042135
## [145,] 0.957946569 0.043934783 -0.571936414
## [146,] 0.631153027 -1.615461736 -0.458493584
## [147,] 0.975146229 2.323115378 -0.458493584
## [148,] -0.444278352 -1.902685138 0.902820383
## [149,] -1.046266456 1.058913102 -0.050099394
## [150,] 0.881000722 -1.508015025 -0.503870716
## [151,] 0.861990571 0.411612186 -0.526559282
## [152,] -0.693220801 1.837770723 -0.208919356
## [153,] 0.855653854 -0.108849198 -0.617313546
## [154,] -1.609329013 1.783785303 -0.186230790
## [155,] 0.677320536 -0.687751111 -0.594624980
## [156,] -0.963889136 0.829606098 5.054827982
## [157,] 0.830306986 -0.189827329 -0.594624980
## [158,] 0.504418690 -1.363879193 0.040654871
## [159,] -0.345606618 -0.476788666 -0.163542224
## [160,] 0.773276535 0.634629627 -0.594624980
## [161,] 0.795907666 -0.765584460 -0.208919356
## [162,] -1.567687731 0.773000026 -0.004722261
## [163,] 0.124215677 0.263807443 -0.662690679
## [164,] -1.497078600 -0.701378498 1.197771743
## [165,] -0.761114196 0.245462882 0.176786268
## [166,] 0.727109026 -0.898451490 0.562491892
## [167,] -0.213440809 0.977934972 -0.526559282
## [168,] 0.719867064 -0.286005238 -0.640002113
## [169,] -0.638906085 -1.459795038 -0.435805018
## [170,] 0.700856913 -0.198999609 -0.458493584
## [171,] 0.594037971 0.184401703 -0.617313546
## [172,] 0.346906013 -0.083428879 -0.435805018
## [173,] 0.669173329 -1.959029145 -0.050099394
## [174,] 0.657405140 0.461928695 -0.617313546
## [175,] 0.639300235 0.135133455 -0.549247848
## [176,] -0.385437410 -0.874079431 -0.004722261
## [177,] 0.625721556 0.450921959 -0.526559282
## [178,] 0.599469443 1.843798222 -0.594624980
## [179,] 0.593132726 -0.650799925 -0.322362187
## [180,] 0.584080273 -0.782356629 0.335606230
## [181,] 0.577743556 -0.590787006 -0.413116451
## [182,] 0.576838311 0.593747464 -0.594624980
## [183,] 0.292591297 -1.003277549 -0.617313546
## [184,] -0.854354459 -1.257218678 1.764985896
## [185,] 0.551491444 -0.227826776 -0.549247848
## [186,] -0.309396807 1.923466027 -0.276985055
## [187,] -1.072518569 -1.430967871 2.445642879
## [188,] 0.374968616 1.137270582 -0.571936414
## [189,] 0.487219030 -0.009002377 -0.435805018
## [190,] 0.530670802 0.362343938 -0.208919356
## [191,] -1.540530373 0.186760289 4.827942321
## [192,] 0.475450841 0.189380941 -0.526559282
## [193,] -1.014582871 0.577237360 1.719608763
## [194,] 0.480882313 -0.607297110 -0.390427885
## [195,] 0.373158126 -2.027952279 0.108720569
## [196,] 0.403031220 0.602919745 -0.413116451
## [197,] 0.404841710 -0.585283638 -0.594624980
## [198,] 0.397599748 -1.430443741 -0.571936414
## [199,] -0.294912883 -0.959512669 -0.254296489
## [200,] 0.362295182 -1.771652564 0.335606230
## [201,] 0.340569296 -0.923609744 -0.594624980
## [202,] 0.320653900 1.043189194 -0.617313546
## [203,] 0.274486391 -1.309893773 -0.617313546
## [204,] 0.155899261 1.133077539 -0.571936414
## [205,] 0.147752054 -0.168862117 -0.163542224
## [206,] 0.305264731 1.076733533 -0.594624980
## [207,] 0.229224128 2.108746086 -0.594624980
## [208,] -0.917721628 1.010168985 0.154097701
## [209,] 0.269960165 0.180208660 -0.571936414
## [210,] 0.277202127 -0.093649420 -0.526559282
## [211,] 0.250950014 0.207987566 -0.435805018
## [212,] 0.233750354 -0.332914900 -0.458493584
## [213,] 0.235560845 -0.051456931 -0.617313546
## [214,] -0.119295301 1.780902586 -0.526559282
## [215,] -0.758398460 -0.916271920 0.607869024
## [216,] 0.226508392 0.806282300 -0.617313546
## [217,] -1.020919588 -1.403451031 1.855740160
## [218,] 0.228318883 -1.545490341 -0.617313546
## [219,] 0.216550694 -0.768467176 -0.367739319
## [220,] -0.618085444 1.233710556 0.131409135
## [221,] 0.119689450 0.563609972 -0.526559282
## [222,] -1.195631925 -0.428568679 0.290229098
## [223,] -1.433711431 1.005189747 2.468331445
## [224,] 0.024638697 -1.160254573 -0.503870716
## [225,] 0.094342583 -1.145840990 -0.571936414
## [226,] 0.054511791 0.569899536 -0.617313546
## [227,] -0.831723327 0.785841218 -0.208919356
## [228,] 0.044554093 -1.322734965 -0.571936414
## [229,] -1.421037997 1.117353631 0.290229098
## [230,] 0.055417036 -1.544180015 0.017966305
## [231,] -0.681452613 0.726876560 0.040654871
## [232,] 0.030070169 -0.053553452 -0.640002113
## [233,] 0.012870509 -0.771087828 -0.526559282
## [234,] -0.128347753 -1.566193488 -0.526559282
## [235,] -0.032391755 -1.680715958 2.218757218
## [236,] -0.008855378 -1.183054241 -0.390427885
## [237,] -0.032391755 0.863412502 -0.367739319
## [238,] -0.039633717 1.499968747 -0.594624980
## [239,] -1.107823134 -0.378252171 -0.549247848
## [240,] -0.078559263 0.510934877 -0.640002113
## [241,] -0.978373061 -0.896617034 0.267540532
## [242,] -0.097569414 1.323860967 -0.299673621
## [243,] -0.894185251 1.602960350 1.084328912
## [244,] -0.206198846 -0.565890817 0.154097701
## [245,] -0.115674319 -0.475740406 -0.594624980
## [246,] -0.437036390 -1.702991495 -0.254296489
## [247,] -1.073423814 -0.911292682 0.653246156
## [248,] -0.120200546 0.447515112 -0.549247848
## [249,] -0.122011036 -0.264253831 -0.435805018
## [250,] -0.134684470 -0.952436910 -0.594624980
## [251,] -0.417120994 0.596630181 -0.617313546
## [252,] -0.133779225 1.696255543 -0.481182150
## [253,] -0.138305451 2.651220943 0.880131817
## [254,] -1.068897588 -1.041801126 -0.027410827
## [255,] -0.165462809 -1.477091337 -0.571936414
## [256,] -0.196241148 -1.847127327 -0.481182150
## [257,] -0.274997487 0.720062866 -0.617313546
## [258,] -0.195335903 0.071451624 -0.481182150
## [259,] -0.274092242 0.883329453 -0.027410827
## [260,] -0.236977186 2.276467781 0.539803325
## [261,] -0.217967035 0.155312471 -0.004722261
## [262,] -0.227924733 -0.761391417 -0.095476526
## [263,] -0.558339256 -1.518759696 -0.481182150
## [264,] -0.340175146 -0.631931234 0.040654871
## [265,] -0.754777479 -0.417299878 0.063343437
## [266,] -0.274997487 0.532948350 -0.617313546
## [267,] -1.574024448 1.930279720 0.766688987
## [268,] -0.657916236 0.445418590 0.721311854
## [269,] -0.502214049 -0.541518758 0.086032003
## [270,] -0.316638769 -2.341644261 -0.503870716
## [271,] -0.315733524 -0.025774546 -0.503870716
## [272,] -0.355564316 -1.181481850 -0.617313546
## [273,] -0.325691222 -0.317977187 -0.231607923
## [274,] -0.426173447 -0.264253831 -0.367739319
## [275,] -0.514887483 -1.189343805 -0.231607923
## [276,] -0.395395108 -0.060629211 -0.503870716
## [277,] -0.437941635 -1.498318614 -0.503870716
## [278,] -0.450615069 -1.745708114 0.539803325
## [279,] -0.438846880 0.518010636 -0.617313546
## [280,] -0.457857031 -0.439051285 -0.367739319
## [281,] -1.698948295 1.449390173 3.330496958
## [282,] -0.418931485 -1.607861846 -0.435805018
## [283,] -0.803660724 1.160070250 -0.481182150
## [284,] -0.452425560 -0.208433955 -0.435805018
## [285,] -0.467814729 -0.420444659 -0.549247848
## [286,] -0.461478012 -1.137979035 -0.276985055
## [287,] -0.618990689 0.756751987 0.721311854
## [288,] -0.770166649 -0.172793094 1.243148875
## [289,] -1.012772381 1.611084370 0.176786268
## [290,] -0.502214049 1.459086584 -0.413116451
## [291,] -0.920437364 -0.941954305 -0.004722261
## [292,] -0.532992388 -0.047525954 1.220460309
## [293,] -0.541139596 0.617857458 1.197771743
## [294,] -0.557434011 0.937576939 0.766688987
## [295,] -0.942163250 -1.473160360 -0.186230790
## [296,] -0.540234351 -1.853154825 -0.549247848
## [297,] -1.253567622 0.502024662 -0.458493584
## [298,] -0.559244501 0.189905071 -0.481182150
## [299,] -0.565581218 -1.210833147 -0.186230790
## [300,] -1.548677580 0.711152651 0.449049061
## [301,] -0.563770728 -0.529463761 -0.503870716
## [302,] -0.585496614 -1.238874118 -0.571936414
## [303,] -0.604506765 0.949369871 -0.503870716
## [304,] -0.622611670 -1.455601995 -0.617313546
## [305,] -0.635285104 -0.734660772 -0.072787960
## [306,] -0.635285104 0.540810304 -0.594624980
## [307,] -0.695936537 -1.930464044 -0.549247848
## [308,] -0.692315556 0.999424314 -0.640002113
## [309,] -0.836249554 0.723469713 -0.640002113
## [310,] -0.886038043 1.109491676 -0.345050753
## [311,] -0.976562570 -1.219743362 -0.276985055
## [312,] -1.022730079 -1.683598674 0.721311854
## [313,] 1.941042931 0.886212170 -0.571936414
## [314,] 1.487515052 1.364743131 -0.413116451
## [315,] 0.838454194 0.312027430 -0.571936414
## [316,] 0.138699601 2.322067117 -0.571936414
## [317,] 1.006829814 1.077781793 -0.549247848
## [318,] -0.215251299 -0.740950336 -0.571936414
## [319,] -1.698948295 -0.453726933 0.403671929
## [320,] 0.439241030 -0.645296557 -0.640002113
## [321,] -0.676926386 0.981865949 -0.435805018
## [322,] 0.084384885 1.269089351 -0.481182150
## [323,] 1.453115731 -1.028173738 -0.594624980
## [324,] 1.403327242 1.173435572 -0.594624980
## [325,] 2.604587713 -1.602358478 -0.322362187
## [326,] -0.617180198 0.120457807 -0.390427885
## [327,] 2.078640212 -0.166765596 -0.458493584
## [328,] 0.174909412 0.312027430 -0.503870716
## [329,] -0.412594768 1.173435572 -0.571936414
## [330,] -0.155505111 0.312027430 0.063343437
## [331,] -1.650970295 -0.453726933 -0.027410827
## [332,] -1.025445815 0.216111586 2.128002953
## [333,] -0.361901033 0.503334988 -0.095476526
## [334,] -1.314219055 0.503334988 0.880131817
## [335,] 1.456736713 0.407681209 -0.594624980
## [336,] 0.649257933 1.364743131 -0.254296489
## [337,] 0.333327334 0.503334988 -0.322362187
## [338,] -1.020014343 -0.358073154 2.899414201
## [339,] 1.425053128 0.886212170 -0.594624980
## [340,] 1.427768864 0.216111586 0.494426193
## [341,] -1.635581126 0.312027430 1.311214573
## [342,] 1.188784113 -0.070849752 -0.526559282
## [343,] -1.170285058 -0.262419375 1.787674462
## [344,] 1.121795963 -1.411050920 1.288526007
## [345,] 0.998682606 -0.262419375 -0.617313546
## [346,] -1.230031245 1.843536156 -0.594624980
## [347,] 0.809486345 0.024804027 0.040654871
## [348,] 0.829401741 0.120457807 -0.526559282
## [349,] 0.848411892 0.312027430 -0.413116451
## [350,] -1.136790983 -0.262419375 -0.254296489
## [351,] -1.077950040 1.460658975 2.672528540
## [352,] 0.722582799 0.216111586 -0.594624980
## [353,] 0.706288385 1.077781793 -0.435805018
## [354,] -0.839870535 0.790558391 -0.435805018
## [355,] 0.380400088 -1.123827517 -0.367739319
## [356,] -0.273186996 1.556312754 -0.231607923
## [357,] 0.584080273 0.694904612 -0.050099394
## [358,] 0.560543896 1.269089351 -0.549247848
## [359,] 0.557828161 -0.453726933 -0.549247848
## [360,] -1.031782532 1.269089351 -0.322362187
## [361,] -1.177527020 -0.932519959 0.517114759
## [362,] 0.316127674 -0.166765596 3.353185524
## [363,] 0.299833259 -0.645296557 -0.594624980
## [364,] -1.411080299 0.790558391 -0.118165092
## [365,] 0.006533792 1.173435572 -0.526559282
## [366,] -1.510657279 0.981865949 -0.435805018
## [367,] 0.257286731 1.269089351 -0.481182150
## [368,] -1.697137804 -0.166765596 2.400265747
## [369,] -0.652484764 -0.836604115 0.267540532
## [370,] -0.744819781 -0.070849752 2.899414201
## [371,] -1.293398414 0.024804027 0.925508949
## [372,] 0.209308732 -1.315397141 -0.594624980
## [373,] 0.167667450 1.077781793 -0.571936414
## [374,] 0.056322282 0.024804027 -0.571936414
## [375,] -0.516697974 0.120457807 -0.345050753
## [376,] -0.398110843 -0.645296557 1.424657404
## [377,] 0.062658998 -1.698274322 -0.231607923
## [378,] -0.678736877 0.886212170 -0.322362187
## [379,] -1.195631925 1.173435572 0.017966305
## [380,] -0.174515262 -1.698274322 -0.072787960
## [381,] -0.017002585 -0.932519959 -0.345050753
## [382,] -1.536004146 0.024804027 2.445642879
## [383,] -0.810902686 -1.315397141 -0.549247848
## [384,] -0.252366355 0.790558391 -0.435805018
## [385,] -0.255987336 0.407681209 -0.571936414
## [386,] -0.238787676 0.312027430 -0.345050753
## [387,] -0.239692921 -0.166765596 2.354888615
## [388,] -0.323880731 -1.028173738 -0.526559282
## [389,] -0.304870581 1.556312754 -0.571936414
## [390,] -0.451520314 1.651966533 -0.050099394
## [391,] -0.429794428 -0.932519959 -0.458493584
## [392,] -0.497687823 1.747620312 -0.640002113
## [393,] -1.561351014 0.120457807 -0.571936414
## [394,] -0.498593068 0.598988767 -0.276985055
## [395,] -0.532992388 -1.411050920 -0.413116451
## [396,] -0.520318955 -0.070849752 -0.367739319
## [397,] -0.533897634 1.269089351 -0.617313546
## [398,] -0.491351106 1.077781793 0.925508949
## [399,] -0.595454312 -0.836604115 1.107017478
## [400,] -0.628948387 -0.645296557 -0.617313546
## [401,] -0.889659024 1.747620312 0.222163400
## [402,] -0.882417062 0.120457807 -0.549247848
## [403,] -0.703178499 1.460658975 -0.163542224
## [404,] -0.747535517 -1.028173738 0.312917664
## [405,] -0.695031292 0.120457807 -0.503870716
## [406,] -1.099675927 -0.453726933 0.290229098
## [407,] -0.714041442 0.312027430 -0.481182150
## [408,] -0.752966989 0.024804027 -0.299673621
## [409,] -0.770166649 -0.740950336 -0.571936414
## [410,] -0.765640423 -1.123827517 -0.390427885
## [411,] -0.723093895 0.024804027 -0.594624980
## [412,] -0.743009291 1.556312754 -0.503870716
## [413,] -0.840775780 -1.506704699 -0.571936414
## [414,] -1.119591323 1.556312754 -0.458493584
## [415,] -0.737577819 -1.123827517 -0.526559282
## [416,] -0.781029592 0.598988767 -0.367739319
## [417,] -1.110538870 0.694904612 -0.549247848
## [418,] -0.852543968 0.216111586 -0.571936414Other examples
Create a matrix
X <- sample(0:200, 100)
Mat <- matrix(X, 50, 50) Obtain the mean value of each row for matrix Mat
apply(Mat, 1, mean)## [1] 57.0 119.0 45.5 79.5 123.0 163.5 17.0 108.5 188.5 90.5 137.0 111.5
## [13] 79.5 108.0 107.0 118.5 80.5 149.5 77.5 113.0 127.0 129.5 34.5 120.0
## [25] 83.0 150.0 93.0 80.0 121.0 80.0 73.0 30.0 95.0 149.5 81.5 108.0
## [37] 154.5 84.5 85.0 83.5 75.0 73.5 113.0 58.0 125.5 96.5 90.0 57.0
## [49] 48.0 142.0Obtain the mean value of each column for matrix Mat
apply(Mat, 2, mean)## [1] 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32
## [11] 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32
## [21] 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32
## [31] 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32
## [41] 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32 96.28 100.32Calculate the sum of each column for matrix Mat
apply(Mat, 2, sum)## [1] 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814
## [16] 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016
## [31] 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814
## [46] 5016 4814 5016 4814 5016Calculate the sum of each row for matrix Mat
apply(Mat, 1, sum)## [1] 2850 5950 2275 3975 6150 8175 850 5425 9425 4525 6850 5575 3975 5400 5350
## [16] 5925 4025 7475 3875 5650 6350 6475 1725 6000 4150 7500 4650 4000 6050 4000
## [31] 3650 1500 4750 7475 4075 5400 7725 4225 4250 4175 3750 3675 5650 2900 6275
## [46] 4825 4500 2850 2400 7100There is no one way of doing things in R!
colSums(Mat)## [1] 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814
## [16] 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016
## [31] 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814 5016 4814
## [46] 5016 4814 5016 4814 5016rowSums(Mat)## [1] 2850 5950 2275 3975 6150 8175 850 5425 9425 4525 6850 5575 3975 5400 5350
## [16] 5925 4025 7475 3875 5650 6350 6475 1725 6000 4150 7500 4650 4000 6050 4000
## [31] 3650 1500 4750 7475 4075 5400 7725 4225 4250 4175 3750 3675 5650 2900 6275
## [46] 4825 4500 2850 2400 7100Check which variables of the pbc data set are numeric
lapply(pbc, is.numeric)## $id
## [1] TRUE
##
## $time
## [1] TRUE
##
## $status
## [1] TRUE
##
## $trt
## [1] TRUE
##
## $age
## [1] TRUE
##
## $sex
## [1] FALSE
##
## $ascites
## [1] TRUE
##
## $hepato
## [1] TRUE
##
## $spiders
## [1] TRUE
##
## $edema
## [1] TRUE
##
## $bili
## [1] TRUE
##
## $chol
## [1] TRUE
##
## $albumin
## [1] TRUE
##
## $copper
## [1] TRUE
##
## $alk.phos
## [1] TRUE
##
## $ast
## [1] TRUE
##
## $trig
## [1] TRUE
##
## $platelet
## [1] TRUE
##
## $protime
## [1] TRUE
##
## $stage
## [1] TRUEObtain the number of missing values per pbc variable
lapply(pbc, function(x) { sum(is.na(x)) } ) ## $id
## [1] 0
##
## $time
## [1] 0
##
## $status
## [1] 0
##
## $trt
## [1] 106
##
## $age
## [1] 0
##
## $sex
## [1] 0
##
## $ascites
## [1] 106
##
## $hepato
## [1] 106
##
## $spiders
## [1] 106
##
## $edema
## [1] 0
##
## $bili
## [1] 0
##
## $chol
## [1] 134
##
## $albumin
## [1] 0
##
## $copper
## [1] 108
##
## $alk.phos
## [1] 106
##
## $ast
## [1] 106
##
## $trig
## [1] 136
##
## $platelet
## [1] 11
##
## $protime
## [1] 2
##
## $stage
## [1] 6Other examples
Obtain the quadratic term of the vector 1:3
Present the results as a list
lapply(1:3, function(x) { x^2 } )## [[1]]
## [1] 1
##
## [[2]]
## [1] 4
##
## [[3]]
## [1] 9Create a list
A <- matrix(1:9, 3,3)
B <- matrix(4:15, 4,3)
C <- matrix(8:10, 3,2)Select elements in a list
MyList <- list(A, B, C) Select the first row of each element
Present the results as a list
lapply(MyList,"[", 1, )## [[1]]
## [1] 1 4 7
##
## [[2]]
## [1] 4 8 12
##
## [[3]]
## [1] 8 8Select the second column of each element
Present the results as a list
lapply(MyList,"[", , 2)## [[1]]
## [1] 4 5 6
##
## [[2]]
## [1] 8 9 10 11
##
## [[3]]
## [1] 8 9 10Obtain the number of missing values per pbc variable
sapply(pbc, function(x) { sum(is.na(x)) } ) ## id time status trt age sex ascites hepato
## 0 0 0 106 0 0 106 106
## spiders edema bili chol albumin copper alk.phos ast
## 106 0 0 134 0 108 106 106
## trig platelet protime stage
## 136 11 2 6Other examples
Obtain the quadratic term of the vector 1:3
Present the results as a vector
sapply(1:3, function(x) { x^2 } )## [1] 1 4 9Note that you can change the output of the sapply format and make it identical to the lapply output by specifying simplify = FALSE
sapply(1:3, function(x) { x^2 }, simplify = FALSE)## [[1]]
## [1] 1
##
## [[2]]
## [1] 4
##
## [[3]]
## [1] 9Obtain the mean age and time per sex
tapply(pbc$age, pbc$sex, mean)## m f
## 55.71072 50.15694tapply(pbc$time, pbc$sex, mean)## m f
## 1894.023 1920.578Obtain the mean age and time (both elements of the variables divided by two) per sex
tapply(pbc$age, pbc$sex, function(x) { mean(x/2) } )## m f
## 27.85536 25.07847tapply(pbc$time, pbc$sex, function(x) { mean(x/2) } )## m f
## 947.0114 960.2888Obtain the mean age and time per sex and status
tapply(pbc$age, list(pbc$status, pbc$sex), mean)## m f
## 0 55.68595 49.02203
## 1 42.16290 41.62939
## 2 57.42174 53.30739tapply(pbc$time, list(pbc$status, pbc$sex), mean)## m f
## 0 2462.176 2322.953
## 1 1147.667 1600.545
## 2 1584.875 1340.504Create a list:
mapply(rep, x = 1:4, times = 4:1)## [[1]]
## [1] 1 1 1 1
##
## [[2]]
## [1] 2 2 2
##
## [[3]]
## [1] 3 3
##
## [[4]]
## [1] 4#### alternative run: list(rep(1, 4), rep(2, 3), rep(3, 2), rep(4, 1))Create a list:
mapply(rep, times = 1:4, x = 4)## [[1]]
## [1] 4
##
## [[2]]
## [1] 4 4
##
## [[3]]
## [1] 4 4 4
##
## [[4]]
## [1] 4 4 4 4#### alternative run: list(rep(4, times = 1), rep(4, times = 2), rep(4, times = 3), rep(4, times = 4))Create a list:
mapply(rep, x = 1:4, times = 4, SIMPLIFY = FALSE)## [[1]]
## [1] 1 1 1 1
##
## [[2]]
## [1] 2 2 2 2
##
## [[3]]
## [1] 3 3 3 3
##
## [[4]]
## [1] 4 4 4 4### alternative run: list(rep(1, 4), rep(2, 4), rep(3, 4), rep(4, 4))Note: if the length is the same we can obtain a simplified output
mapply(rep, x = 1:4, times = 4, SIMPLIFY = TRUE)## [,1] [,2] [,3] [,4]
## [1,] 1 2 3 4
## [2,] 1 2 3 4
## [3,] 1 2 3 4
## [4,] 1 2 3 4### alternative run: matrix(c(rep(1, 4), rep(2, 4), rep(3, 4), rep(4, 4)), 4, 4)Other examples
mapply(function(x,y) { seq_len(x) + y },
c(a = 1, b = 2, c = 3),
c(A = 10, B = 0, C = -10))## $a
## [1] 11
##
## $b
## [1] 1 2
##
## $c
## [1] -9 -8 -7#### alternative run: list(c(1) + 10, c(1, 2) + 0, c(1, 2, 3) - 10)Note!
mapply(mean, MyList)## [1] 5.0 9.5 9.0sapply(MyList, mean)## [1] 5.0 9.5 9.0Let’s assume that only the long format data set pbcseq is available
We want to obtain the mean serum bilirubin of the last follow-up measurement (specified as day) per status group
Each patient is counted once!
head(pbcseq)Sort data
pbcseq <- pbcseq[order(pbcseq$id, pbcseq$day), ]Select the last follow-up measurement of each patient
pbcseq.idNEW2 <- pbcseq[tapply(rownames(pbcseq), pbcseq$id, tail, 1), ]Step by step
tapply(rownames(pbcseq), pbcseq$id, tail, 1)## 1 2 3 4 5 6 7 8 9 10 11
## "2" "11" "15" "22" "28" "34" "41" "49" "56" "57" "69"
## 12 13 14 15 16 17 18 19 20 21 22
## "71" "83" "90" "101" "114" "117" "118" "133" "137" "149" "152"
## 23 24 25 26 27 28 29 30 31 32 33
## "154" "167" "179" "185" "186" "189" "199" "202" "214" "230" "240"
## 34 35 36 37 38 39 40 41 42 43 44
## "254" "258" "269" "271" "281" "289" "304" "308" "324" "339" "350"
## 45 46 47 48 49 50 51 52 53 54 55
## "359" "367" "374" "383" "387" "396" "406" "415" "418" "423" "429"
## 56 57 58 59 60 61 62 63 64 65 66
## "435" "446" "462" "469" "482" "496" "506" "509" "515" "521" "534"
## 67 68 69 70 71 72 73 74 75 76 77
## "544" "558" "562" "575" "586" "592" "607" "611" "616" "617" "619"
## 78 79 80 81 82 83 84 85 86 87 88
## "623" "634" "638" "648" "658" "673" "676" "687" "688" "690" "694"
## 89 90 91 92 93 94 95 96 97 98 99
## "698" "707" "710" "711" "726" "729" "730" "744" "748" "762" "775"
## 100 101 102 103 104 105 106 107 108 109 110
## "779" "791" "803" "804" "814" "824" "829" "840" "848" "858" "865"
## 111 112 113 114 115 116 117 118 119 120 121
## "873" "884" "889" "900" "912" "923" "928" "935" "937" "945" "946"
## 122 123 124 125 126 127 128 129 130 131 132
## "956" "958" "959" "968" "973" "984" "989" "1001" "1007" "1011" "1017"
## 133 134 135 136 137 138 139 140 141 142 143
## "1026" "1038" "1048" "1057" "1069" "1075" "1081" "1093" "1096" "1105" "1108"
## 144 145 146 147 148 149 150 151 152 153 154
## "1112" "1116" "1123" "1128" "1134" "1137" "1146" "1157" "1160" "1170" "1171"
## 155 156 157 158 159 160 161 162 163 164 165
## "1174" "1178" "1189" "1198" "1202" "1210" "1221" "1222" "1225" "1226" "1231"
## 166 167 168 169 170 171 172 173 174 175 176
## "1239" "1245" "1255" "1260" "1261" "1271" "1278" "1287" "1297" "1307" "1313"
## 177 178 179 180 181 182 183 184 185 186 187
## "1314" "1320" "1323" "1333" "1334" "1339" "1347" "1352" "1357" "1361" "1365"
## 188 189 190 191 192 193 194 195 196 197 198
## "1373" "1378" "1382" "1383" "1393" "1397" "1402" "1403" "1411" "1420" "1428"
## 199 200 201 202 203 204 205 206 207 208 209
## "1431" "1442" "1452" "1454" "1463" "1471" "1476" "1484" "1491" "1494" "1496"
## 210 211 212 213 214 215 216 217 218 219 220
## "1506" "1514" "1520" "1522" "1526" "1530" "1537" "1541" "1551" "1557" "1562"
## 221 222 223 224 225 226 227 228 229 230 231
## "1570" "1574" "1575" "1583" "1592" "1601" "1605" "1609" "1612" "1616" "1620"
## 232 233 234 235 236 237 238 239 240 241 242
## "1624" "1625" "1627" "1629" "1631" "1633" "1636" "1639" "1647" "1651" "1659"
## 243 244 245 246 247 248 249 250 251 252 253
## "1661" "1665" "1667" "1673" "1677" "1685" "1688" "1690" "1691" "1694" "1702"
## 254 255 256 257 258 259 260 261 262 263 264
## "1706" "1712" "1718" "1721" "1729" "1734" "1735" "1741" "1744" "1749" "1753"
## 265 266 267 268 269 270 271 272 273 274 275
## "1757" "1764" "1765" "1767" "1774" "1777" "1785" "1791" "1794" "1799" "1803"
## 276 277 278 279 280 281 282 283 284 285 286
## "1805" "1810" "1815" "1822" "1829" "1830" "1834" "1838" "1845" "1846" "1848"
## 287 288 289 290 291 292 293 294 295 296 297
## "1852" "1854" "1858" "1865" "1870" "1873" "1875" "1882" "1884" "1887" "1890"
## 298 299 300 301 302 303 304 305 306 307 308
## "1893" "1894" "1896" "1899" "1904" "1908" "1909" "1914" "1916" "1921" "1926"
## 309 310 311 312
## "1931" "1936" "1940" "1945"### alternative run: pbcseq.idNEW2 <- pbcseq[!duplicated(pbcseq[c("id")], fromLast = TRUE), ]Obtain the mean serum bilirubin per status group
tapply(pbcseq.idNEW2$bili, pbcseq.idNEW2$status, mean)## 0 1 2
## 2.190909 9.172414 11.800000