njtynhj

I have the following dataframe

I want to subset this dataset such that I will only have rows between the first record and the the first 1 value in the flag column for each group and if there is no 1, that group should not appear at all.

Something like this:

I saw some answers at Dplyr : how to find the first-non missing string by groups?
But it is for non-missing and I have both non-missing and 0 values.

Or in dplyr (same result)

Data used:

Benchmark Output:

Benchmark code:

Using dplyr::slice, then the equivalent base R using by. And finally one just for performance, with benchmark. All robust for the case with no Flag==1 in a group.

dplyr

base

base fast

benchmark

I did the benchmark on @Lebatsnok modified input, that I remodified because the NAs were not properly recognized as such. MKR's and WWW's solutions are not robust for this case, but i left them in the benchmark anyway.

data

benchmark code

A cumsum based solution using dplyr can be as:

Data:

A solution using dplyr and cumsum.

DATA

With base R, one could, for instance, do this.

First of all, we need a complete test case with a group having no "1" in the "Flag" column:

Now let's define a function that would take in a data frame and return NULL if there no 1 in $Flag and the first N rows otherwise (where N is the number of the row where 1 first occurs). This could be done using which.max with a boolean (TRUE if $Flag is 1, FALSE otherwise):

Now we need to split the data frame by ID, apply the function, and rbind the parts again:

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