dataframe - R padding time series with grouping -


i have data frame columns action, type, project_id, week, events_in_time

i want run analysis on each subgroup defined action, type. have problem padding time series (column week). projects don't have entry given week.

how can add 0 values in events_in_time missing weeks in projects?

i tried merging described here: https://bocoup.com/weblog/padding-time-series-with-r generating weeks , merging nothing happens. understand need generate projects can't find how it. did:

all.week.frame=data.frame(week=seq(0,12)) # fills first 12 weeks merged=merge(data, all.week.frame, all=t)

example data: http://pastebin.com/au3efbga

save file , load with

data= read.table("merged.csv", header = true, sep = ",")

update: found using 

complete(data_filtered, nesting(type,action, project_id), week, fill = list(events_in_time = 0))

solves it

i think complete tidyr looking for. takes data.frame, followed columns complete (things make sure match up), list of values insert if combination missing. here, takes df, makes combinations of week , project_id, fills other column (events_in_time) 0 whenever there no entry.

complete(df, week, project_id, fill = list(events_in_time = 0))

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