RcppRoll | Fast rolling functions through Rcpp | Build Tool library

I am trying to use the mutate function to form three new columns to my data. I have tried defining some of the data and it has not changed it. I have looked at previous examples but all seem to use a group function before using mutate. I think I do not need to create a group before using mutate as it would not fit with my data.

Here is the R code I am using:

I have a unique problem where I need to calculate input values behind a vector of rolling sums. For example, I have an hourly data feed from a sensor as follows:

I have a data.frame df with many groups (series) where the data area are presented annually. I'm trying to create a new column where diff is the difference between area in row 1 and row 2. But I need continue subtracting from the "new" difference. This needs to be done in descending order by year for each series.

I'm trying to calculate the rolling mean of the previous k non-NA values within the dplyr/tidyverse framework. I've written a function that seems to work but was wondering if there's already a function from some package (which will probably be much more efficient than my attempt) doing exactly this. An example dataset:

I am trying to carry a value in one column backwards by a number of rows given in a second column and fill everything in between.

So column y mainly has 1s in it but might have individual numbers up to about 20 (in my real data, up to 3 in my example below). If the number in y is 20, I need the 19 rows before that row and that row itself to equal the value of x for the row where y is 20. If the value in y is 1 the output will just equal x.

y also has many NAs, these NAs are either legitimate NAs where I want an NA output or are placeholders where the filling should occur if a y value afterwards is > 1.

I thought I could use dplyr::lead but I cannot have a variable n value to look forwards a different number of steps, and it wouldn't fill inbetween, and I wondered about making a new, always increasing column and using RcppRoll::roll_max but have similar problems with the flexible window size.

Typically y-values in the lead up to a y > 1 will be 0 or NA, but if there were conflicts I would want to adopt the later value still eg in row 8 of my data frame y is 1 followed by y = 2 in row 9 so I want the value associated with row 9 in both cases. If y in NA and there is not covered by filling backwards, I want it to remain NA (or 0 would be fine)

Thanks for any thoughts

I'm trying to sum up the values in a data.frame in a cumulative way.

I have this:

There must be an easy, possible recursive solution, for the following problem. I would very much appreciate, if anyone can help:

I use data.table and RcppRoll to calculate the weekly sales in qualified weeks within the past 26 weeks for each product. With a window of 26, this works fine, as long as # of current week > 26. However, when # of current week is <= 26, I want to use a window of size 26, 25, ..., and so on.

The formular would be: baseline sales = sum over 26 (or less) weeks of sales (before current week, in qualified weeks only), divided by # of qualified weeks

Here is some code to create test data: