r - Calculations on selected groups of variables -


i have dataframe variable names looking like: 

a.1, a.3,  a.5,  a.6,  a.9, a.10, a.12  b.1, b.3,  b.5,  b.6,  b.9, b.10, b.12

and on j.

the variables' names represent assessed parameters , visit number in longitudinal study.

the dataframe contains fixed baseline parameters.

i create new variables represent changes since last visit each parameter: 

delta.a.3 <- a.3 - a.1 delta.a.5 <- a.5 - a.3

and on visits parameters.

is there way perform task automatically?

here extract dataframe: 

      id      diab    age 20mpace.0 20mpace.1 20mpace.3 20mpace.5 kooskpl.0 kooskpl.1 kooskpl.3 kooskpl.5 1 9000099       0     59    1.3280    1.2946    1.3500    1.2772    100.00     88.89     80.56     83.33 2 9000296       0     69    1.3658    1.3142        na    1.3944    100.00    100.00    100.00    100.00 3 9000622       0     71    1.4305    1.5178        na        na    100.00    100.00        na        na 4 9000798       0     56    1.0636    1.2342    1.1969    1.1572     59.38     59.38     65.63     59.38 5 9001104       0     72    1.3924    1.3473        na        na    100.00    100.00     83.33        na 6 9001400       0     75    1.6203    1.5015    1.5051    1.4264    100.00    100.00    100.00     91.67

id, diab, age - "stationary" baseline parameters. 20mpace.0, 20mpace.1, 20mpace.3, 20mpace.5 - observations of 20mpace on timepoints 0, 1, 3, 5. kooskpl.0, kooskpl.1 kooskpl.3, , kooskpl.5 - observations of kooskpl on timepoints 0, 1, 3, 5.

what do:

  1. to calculate changes in parameters on different timepoints in comparison previous timepoint

    20mpace.1-20mpace.0

    20mpace.3- 20mpace.1

    20mpace.5-20mpace.3

    kooskpl.1 - kooskpl.0

    kooskpl.3 - kooskpl.1

    kooskpl.5 - kooskpl.3

  2. to place results in corresponding columns:

    delta.20mpace.1

    delta.20mpace.3

    delta.20mpace.5.

    delta.kooskpl.1

    delta.kooskpl.3

    delta.kooskpl.5

  3. to calculate changes in parameters on different timepoints in relation timepoint 0:

    20mpace.1-20mpace.0

    20mpace.3- 20mpace.0

    20mpace.5-20mpace.0

    kooskpl.1 - kooskpl.0

    kooskpl.3 - kooskpl.0

    kooskpl.5 - kooskpl.0

  4. again, place results in columns:

    delta0.20mpace.1

    delta0.20mpace.3

    delta0.20mpace.5.

    delta0.kooskpl.1

    delta0.kooskpl.3

    delta0.kooskpl.5

i did not ask last 2 questions in first instance.

may point make loop work selectively on variables same prefix (e.g. 20mpace.0, 20mpace.1, 20mpace.3 , 20mpace.5)? there way it?

i appreciate prompt , informative comments have made! however, beginner need time process information , still not understand told me.

thanks again.

i see 2 possibilities in want, you're not clear in question. possibility #1 maxim k has assumed, diff across each row full data.frame. possibility #2 want diff across each row by group ("a" "j").

before start, here's sample data. i've done groups "a" , "b".

set.seed(1) mydf <- data.frame(matrix(sample(100, 50, replace = true), ncol = 10)) names(mydf) <- paste(rep(c("a", "b"), each = 5), c(1, 3, 5, 7, 9), sep = ".") mydf #   a.1 a.3 a.5 a.7 a.9 b.1 b.3 b.5 b.7 b.9 # 1  27  90  21  50  94  39  49  67  83  79 # 2  38  95  18  72  22   2  60  80  65   3 # 3  58  67  69 100  66  39  50  11  79  48 # 4  91  63  39  39  13  87  19  73  56  74 # 5  21   7  77  78  27  35  83  42  53  70

possibility #1

mydf[-1] - mydf[-length(mydf)] #   a.3 a.5 a.7 a.9 b.1 b.3 b.5 b.7 b.9 # 1  63 -69  29  44 -55  10  18  16  -4 # 2  57 -77  54 -50 -20  58  20 -15 -62 # 3   9   2  31 -34 -27  11 -39  68 -31 # 4 -28 -24   0 -26  74 -68  54 -17  18 # 5 -14  70   1 -51   8  48 -41  11  17

possibility #2

lapply(letters[1:2],         function(x) {          temp <- mydf[grepl(paste("^", x, sep = ""), names(mydf))]           temp[-1] - temp[-length(temp)]        }) # [[1]] #   a.3 a.5 a.7 a.9 # 1  63 -69  29  44 # 2  57 -77  54 -50 # 3   9   2  31 -34 # 4 -28 -24   0 -26 # 5 -14  70   1 -51 #  # [[2]] #   b.3 b.5 b.7 b.9 # 1  10  18  16  -4 # 2  58  20 -15 -62 # 3  11 -39  68 -31 # 4 -68  54 -17  18 # 5  48 -41  11  17

of course, started, because i'm not @ clear on end goal here.


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