How to compute a "cumulative" in a dataframe (without a for loop)

hmmm interesting… it does look like something sneaks in that has a row count of 10… well at least the arrays arent crazy…i am.

df that works:

2×7 DataFrame
 Row │ variable     mean        min     median      max     nmissing  eltype
     │ Symbol       Float64     Signed  Float64     Signed  Int64     Type
─────┼──────────────────────────────────────────────────────────────────────────────────────
   1 │ xxxxxID       6.29382e5  600339   6.33712e5  634550         0  Union{Missing, Int32}
   2 │ nrow         58.9706         50  60.0            60         0  Int64

df that fails:

2×7 DataFrame
 Row │ variable     mean        min     median    max     nmissing  eltype
     │ Symbol       Float64     Signed  Float64   Signed  Int64     Type
─────┼────────────────────────────────────────────────────────────────────────────────────
   1 │ xxxxxID	     6.29566e5  600339  633750.0  634628         0  Union{Missing, Int32}
   2 │ nrow         58.539          10      60.0      60         0  Int64

guess that leads to next question - can you use @chain count functions to mass remove anything that counts below window span in the transform function, all in the same linq call?