If you are using the package for the first time, you will first have to install it.
# install.packages("survival") If you have already downloaded these packages in the current version of R, you will only have to load the packages.
library(survival)## Warning: package 'survival' was built under R version 4.0.4Load a data set from a package.
You can use the double colon symbol (:), to return the pbc object from the package survival. We store this data set to an object with the name pbc.
pbc <- survival::pbcPrint the first 6 rows of the data set using the function head().
head(pbc)View the data set:
View(pbc)If I run “Hello” I get the following:
"Hello"## [1] "Hello"In order to obtain this word again, we will have to retype it. Alternatively, I can assign the string “Hello” to a new object named hi:
hi <- "Hello"Then we can print this word whenever we type hi.
hi## [1] "Hello"Make sure that you have defined the object before you use it.
E.g. number and x will not be found since we did not define them. We can only call them after we have defined them.
# number
number <- 10
number## [1] 10# x
x <- 1
x## [1] 1= is different from ==, e.g. x == 3 is asking a question to R. The single = is equal to <-. pbc$Age will not run because there is a typo.names():names(pbc)## [1] "id" "time" "status" "trt" "age" "sex"
## [7] "ascites" "hepato" "spiders" "edema" "bili" "chol"
## [13] "albumin" "copper" "alk.phos" "ast" "trig" "platelet"
## [19] "protime" "stage"The correct name is age and not Age.
pbc$age## [1] 58.76523 56.44627 70.07255 54.74059 38.10541 66.25873 55.53457 53.05681
## [9] 42.50787 70.55989 53.71389 59.13758 45.68925 56.22177 64.64613 40.44353
## [17] 52.18344 53.93018 49.56057 59.95346 64.18891 56.27652 55.96715 44.52019
## [25] 45.07324 52.02464 54.43943 44.94730 63.87680 41.38535 41.55236 53.99589
## [33] 51.28268 52.06023 48.61875 56.41068 61.72758 36.62697 55.39220 46.66940
## [41] 33.63450 33.69473 48.87064 37.58248 41.79329 45.79877 47.42779 49.13621
## [49] 61.15264 53.50856 52.08761 50.54073 67.40862 39.19781 65.76318 33.61807
## [57] 53.57153 44.56947 40.39425 58.38193 43.89870 60.70637 46.62834 62.90760
## [65] 40.20260 46.45311 51.28816 32.61328 49.33881 56.39973 48.84600 32.49281
## [73] 38.49418 51.92060 43.51814 51.94251 49.82615 47.94524 46.51608 67.41136
## [81] 63.26352 67.31006 56.01369 55.83025 47.21697 52.75838 37.27858 41.39357
## [89] 52.44353 33.47570 45.60712 76.70910 36.53388 53.91650 46.39014 48.84600
## [97] 71.89322 28.88433 48.46817 51.46886 44.95003 56.56947 48.96372 43.01711
## [105] 34.03970 68.50924 62.52156 50.35729 44.06297 38.91034 41.15264 55.45791
## [113] 51.23340 52.82683 42.63929 61.07050 49.65640 48.85421 54.25599 35.15127
## [121] 67.90691 55.43600 45.82067 52.88980 47.18138 53.59890 44.10404 41.94935
## [129] 63.61396 44.22724 62.00137 40.55305 62.64476 42.33539 42.96783 55.96167
## [137] 62.86105 51.24983 46.76249 54.07529 47.03628 55.72621 46.10267 52.28747
## [145] 51.20055 33.86448 75.01164 30.86379 61.80424 34.98700 55.04175 69.94114
## [153] 49.60438 69.37714 43.55647 59.40862 48.75838 36.49281 45.76044 57.37166
## [161] 42.74333 58.81725 53.49760 43.41410 53.30595 41.35524 60.95825 47.75359
## [169] 35.49076 48.66256 52.66804 49.86995 30.27515 55.56742 52.15332 41.60986
## [177] 55.45243 70.00411 43.94251 42.56810 44.56947 56.94456 40.26010 37.60712
## [185] 48.36140 70.83641 35.79192 62.62286 50.64750 54.52704 52.69268 52.72005
## [193] 56.77207 44.39699 29.55510 57.04038 44.62697 35.79740 40.71732 32.23272
## [201] 41.09240 61.63997 37.05681 62.57906 48.97741 61.99042 72.77207 61.29500
## [209] 52.62423 49.76318 52.91444 47.26352 50.20397 69.34702 41.16906 59.16496
## [217] 36.07940 34.59548 42.71321 63.63039 56.62971 46.26420 61.24298 38.62012
## [225] 38.77070 56.69541 58.95140 36.92266 62.41478 34.60917 58.33539 50.18207
## [233] 42.68583 34.37919 33.18275 38.38193 59.76181 66.41205 46.78987 56.07940
## [241] 41.37440 64.57221 67.48802 44.82957 45.77139 32.95003 41.22108 55.41684
## [249] 47.98084 40.79124 56.97467 68.46270 78.43943 39.85763 35.31006 31.44422
## [257] 58.26420 51.48802 59.96988 74.52430 52.36413 42.78713 34.87474 44.13963
## [265] 46.38193 56.30938 70.90760 55.39493 45.08419 26.27789 50.47228 38.39836
## [273] 47.41958 47.98084 38.31622 50.10815 35.08830 32.50376 56.15332 46.15469
## [281] 65.88364 33.94387 62.86105 48.56400 46.34908 38.85284 58.64750 48.93634
## [289] 67.57290 65.98494 40.90075 50.24504 57.19644 60.53662 35.35113 31.38125
## [297] 55.98631 52.72553 38.09172 58.17112 45.21013 37.79877 60.65982 35.53457
## [305] 43.06639 56.39151 30.57358 61.18275 58.29979 62.33265 37.99863 33.15264
## [313] 60.00000 64.99932 54.00137 75.00068 62.00137 43.00068 46.00137 44.00000
## [321] 60.99932 64.00000 40.00000 63.00068 34.00137 52.00000 48.99932 54.00137
## [329] 63.00068 54.00137 46.00137 52.99932 56.00000 56.00000 55.00068 64.99932
## [337] 56.00000 47.00068 60.00000 52.99932 54.00137 50.00137 48.00000 36.00000
## [345] 48.00000 70.00137 51.00068 52.00000 54.00137 48.00000 66.00137 52.99932
## [353] 62.00137 59.00068 39.00068 67.00068 58.00137 64.00000 46.00137 64.00000
## [361] 40.99932 48.99932 44.00000 59.00068 63.00068 60.99932 64.00000 48.99932
## [369] 42.00137 50.00137 51.00068 36.99932 62.00137 51.00068 52.00000 44.00000
## [377] 32.99932 60.00000 63.00068 32.99932 40.99932 51.00068 36.99932 59.00068
## [385] 55.00068 54.00137 48.99932 40.00000 67.00068 68.00000 40.99932 68.99932
## [393] 52.00000 56.99932 36.00000 50.00137 64.00000 62.00137 42.00137 44.00000
## [401] 68.99932 52.00000 66.00137 40.00000 52.00000 46.00137 54.00137 51.00068
## [409] 43.00068 39.00068 51.00068 67.00068 35.00068 67.00068 39.00068 56.99932
## [417] 58.00137 52.99932Use the function is.na() to check if an object consists of missing values:
is.na(x)## [1] FALSEUse the is.null() function to check for Null data:
is.null(pbc$age)## [1] FALSEUse the is.infinite() function to check for infinity data:
is.infinite(pbc$age)## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
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