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I want to write a function that rearranges a vector in ascending or descending order. I know I can use sort and order functions but I want to do it manually.
If you want to practice writing your own sorting function, here is a example which applies a recursion approach:
mysort <- function(v, descending = F) {
if (length(v)==1) return(v)
if (descending) return(c(max(v),mysort(v[-which.max(v)],descending = descending)))
return(c(min(v),mysort(v[-which.min(v)])))
}
EXAMPLE
v <- c(1,2,5,4,2,7)
# ascending manner
mysort(v)
# descending manner
mysort(v,descending = T)
such that
> mysort(v)
[1] 1 2 2 4 5 7
> mysort(v,descending = T)
[1] 7 5 4 2 2 1
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I want to create an integer vector in R with size n+1, but R cant understand that with "n" i mean all the natural numbers.
Something like this:
n = 1:10
my_vector <- n+1
my_vector
[1] 2 3 4 5 6 7 8 9 10 11
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Prompted:
Given a vector of integers, write a function that returns a vector of those unique integers with multiple occurrences and put the result in a data frame.
I do not know how to isolate integers with multiple occurrences. Perhaps using the unique function?
I guess I would then want to display the results with something like:
table()
as.data.frame(table())
Any help would be much appreciated!
> sample(1:10, 10, replace=TRUE) -> x
> x
[1] 5 3 2 10 10 5 9 5 5 6
> y <- rle(sort(x))
> y$values[y$lengths > 1]
[1] 5 10
> y$lengths[y$lengths > 1]
[1] 4 2
Or using table:
> table(x)[table(x) > 1]
x
5 10
4 2
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I need to write an R program that, given a vector, will return another vector giving the number of elements from each position in the input vector to the occurrence in the input vector of a specified value. For example, if the specified value is 0, then with:
input : x<-c(1,1,0,1,1,1,0)
desired output<- (2,1,0,3,2,1,0)
Thanks in advance :)
We can try
library(data.table)
ave(x, rleid(x), FUN= function(x) rev(seq_along(x)))*x
#[1] 2 1 0 3 2 1 0
We could also use rle from base R
rl <- inverse.rle(within.list(rle(x), values <- seq_along(values)))
ave(x, rl, FUN=function(x) rev(seq_along(x)))*x
#[1] 2 1 0 3 2 1 0
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I have a table like so:
1 2 3 4 5
a b a c
b b
a a a a
c b c b
Is there a special syntax to use for either Filter or Reduce (or something else entirely?) to get it so only the rows with an 'a' (including blanks) are shown? Likewise, is there a built-in way to count the frequency of 'a' for each column or would I have to loop over those individually?
Can't think of a way to pass rows or columns to Reduce or Filter to achieve the first, although a data.frame might get passed in a column-wise fashion for the second question since it is a list of columns. apply is the usual mechanism for doing row-wise operations, but I can think of quicker methods. For the first, under the assumption it is named X and is either a matrix or a data.frame:
X[ rowSums(X=="a", na.rm-TRUE) > 0 , ]
For the second:
colSums( X == "a")
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I have a table with two variables.The data is from NMR.So when I plot I get a spectrum.I found the peaks in plot.But I need to know how to list the values of peak and store them into a variable.Anyone please help.
An easy implementation based on Brian Ripley's post at R-help:
peaks <- function(x, halfWindowSize) {
windowSize <- halfWindowSize * 2 + 1
windows <- embed(x, windowSize)
localMaxima <- max.col(windows, "first") == halfWindowSize + 1
return(c(rep(FALSE, halfWindowSize), localMaxima, rep(FALSE, halfWindowSize)))
}
Example:
x <- c(1,3,1,3,1)
peaks(x, 1)
## [1] FALSE TRUE FALSE TRUE FALSE