R中数据框行中的子集

Question

I have a data frame with 30 rows and 4 columns (namely, x, y, z, u ). It is given below.

mydata = data.frame(x = rnorm(30,4), y = rnorm(30,2,1), z = rnorm(30,3,1), u = rnorm(30,5))

Further, I have a sequence values, which represent row number in my data frame.

myseq = c(seq(1, 30, by = 5))
myseq
[1]  1  6 11 16 21 26

Now, I wanted to compute the prob values for each segment of 99 rows.

filt= subset(mydata[1:6,], mydata[1:6,]$x < mydata[1:6,]$y & mydata[1:6,]$z < mydata[1:6,]$u
filt
prob = length(filt$x)/30
prob

Then I need to compute the above prob for 1:6 ,.., 27:30 and so on . Here, I have only 6 prob values. So, I can do one by one. If I have 100 values it would be tedious. Are there any way to compute the prob values?.

Thank you in advance.

Answer 1

BTW: in subset(DF[1:99,], ...) , use DF[1:99,] in the first argument, not again, ala

subset(DF[1:99,], cumsuml < inchivaluel & cumsumr < inchivaluer)

Think about how to do this in a list .

1. The first step is to break your data into the va starting points. I'll start with a list of the indices to break it into:

    inds <- mapply(seq, va, c(va[-1], nrow(DF)), SIMPLIFY=FALSE)

   this now is a list of sequences, starting with 1:99 , then 100:198 , etc. See str(inds) to verify.

2. Now we can subset a portion of the data based on each element's vector of indices:

    filts <- lapply(inds, function(ind) subset(DF[ind,], cumsuml < inchivaluel & cumsumr < inchivaluer))

3. We now have a list of vectors, let's summarize it:

    results <- sapply(filts, function(filt) length(filt$cumsuml)/length(alpha))

Bottom line, it helps to think about how to break this problem into lists, examples at http://stackoverflow.com/a/24376207/3358272 .

BTW: instead of initially making a list of indices, we could just break up the data in that first step, ala

DF2 <- mapply(function(a,b) DF[a:b,], va, c(va[-1], nrow(DF)), SIMPLIFY=FALSE)
filts <- lapply(DF2, function(x) subset(x, cumsuml < inchivaluel & cumsumr < inchivaluer))
results <- sapply(filts, function(filt) length(filt$cumsuml)/length(alpha))