## pick elements cumulatively from a vector in R

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I'm using the following to cumulatively (i.e., *first pick first 2 elements and each time add 1 more; see output below*) pick elements from vector `mods`

below. I wonder if there is a faster or simpler approach to doing this in BASE R?

n <- names(mtcars) # BASE R dataset lapply(seq_along(n)[-1], function(i)n[seq_len(i)]) # any faster or simpler approach here? [[1]] [1] "mpg" "cyl" [[2]] [1] "mpg" "cyl" "disp" [[3]] [1] "mpg" "cyl" "disp" "hp" [[4]] [1] "mpg" "cyl" "disp" "hp" "drat"

You could use `Reduce`

:

Reduce(c, n, accumulate=TRUE)

or, to start with the first two elements:

Reduce(c, tail(n,-2), n[1:2], accumulate=TRUE)

It is simpler IMHO, but not faster:

microbenchmark( lapply=lapply(seq_along(n)[-1], function(i)n[seq_len(i)]), Reduce=Reduce(c, n, accumulate=TRUE) ) Unit: microseconds expr min lq mean median uq max neval lapply 10.2 10.6 22.056 10.8 11.0 1119.8 100 Reduce 10.1 10.4 10.865 10.6 10.8 17.5 100

**Cumulative Sums, Products, and Extremes,** Returns a vector whose elements are the cumulative sums, products, minima or maxima of the elements of the argument. Usage. cumsum(x) cumprod(x) cummax (� Vector is a basic data structure in R. It contains element of the same type. The data types can be logical, integer, double, character, complex or raw. A vector’s type can be checked with the typeof() function. Another important property of a vector is its length.

Here is an option with `rep`

and `split`

split(n[sequence(seq_along(n))], rep(seq_along(n), seq_along(n)))

**R: Cumulative sum & product of elements of vector via cumsum ,** R: Cumulative sum & product of elements of vector via cumsum & Free To Choose Duration: 17:50
Posted: Oct 17, 2019 R Sample Dataframe: Randomly Select Rows In R Dataframes. Up till now, our examples have dealt with using the sample function in R to select a random subset of the values in a vector. It is more likely you will be called upon to generate a random sample in R from an existing data frames, randomly selecting rows from the larger set of observations.

I recommend runner package and `window_run`

function which does exactly what you asking for. You can also specify number (`k`

) of elements you'd like to be returned in each window. You can also specify `lag`

and make windows depending on date. Here is example:

library(runner) window_run(names(mtcars)) # [[1]] # [1] "mpg" # # [[2]] # [1] "mpg" "cyl" # # [[3]] # [1] "mpg" "cyl" "disp" # # [[4]] # [1] "mpg" "cyl" "disp" "hp"

In benchmark it's very similar to `Reduce`

solution, because of cpp implementation:

microbenchmark::microbenchmark( window_run = window_run(names(mtcars)), Reduce = Reduce(c, n, accumulate = TRUE), lapply = lapply(seq_along(n)[-1], function(i) n[seq_len(i)]), times = 1000000L ) # Unit: microseconds # expr min lq mean median uq max neval # window_run 10.296 12.782 15.45241 13.543 14.467 98018.87 1e+06 # Reduce 10.979 13.048 15.80921 13.882 14.847 98881.51 1e+06 # lapply 11.797 14.540 17.42722 15.518 16.729 116346.98 1e+06

For more details checkout documentation

**R tutorials,arrays,frames,sort,which,append,subset,merge,filter,** We will apply a filter to select elements which are not NA's and at the same time Given a vector of numbers, we can find the cumulative sum and cumulative� To extract a specific element from a vector, use square brackets. To get the tenth element of letters, for example, use the following: > letters[10] [1] "j" To get the last three elements of LETTERS, use the following: > LETTERS[24:26] [1] "X" "Y" "Z" The colon operator (:) in R is a handy way of creating sequences, so 24:26 results in 25, 25

**Cumulative sum - MATLAB cumsum,** If A is a vector, then cumsum(A) returns a vector containing the cumulative sum of the elements of A . If A is a matrix, then cumsum(A) returns a matrix containing� How R does indexing. Every time R shows you a vector, it displays a number such as [1] in front of the output. In this example, [1] tells you where the first position in your vector is. This number is called the index of that value. If you make a longer vector — say, with the numbers from 1 to 30 — you see more indices. Consider this example:

**How can I find the cumulative sum of a vector without using the ,** If I have [4 -2 6 1 2], how I find the cum sum of this vector without using the cumsum function or loops or any other functions. I method I am� Your list will often be built out of numerous elements and components. Therefore, getting a single element, multiple elements, or a component out of it is not always straightforward. One way to select a component is using the numbered position of that component. For example, to "grab" the first component of shining_list you type . shining_list[[1]]

**Window functions • dplyr,** The output of a window function depends on all its input values, so window functions Cumulative aggregates: cumsum() , cummin() , cummax() (from base R), and R's vector recycling makes it easy to select values that are higher or lower� By Andrie de Vries, Joris Meys . You can extract components from lists in R. Consider two lists. The display of both the unnamed list baskets.list and the named list baskets.nlist show already that the way to access components in a list is a little different.