Question

I have a data frame like this:

FisherID    Year    Month   VesselID
1   2000    1   56
1   2000    1   81
1   2000    2   81
1   2000    3   81
1   2000    4   81
1   2000    5   81
1   2000    6   81
1   2000    7   81
1   2000    8   81
1   2000    9   81
1   2000    10  81
1   2001    1   56
1   2001    2   56
1   2001    3   81
1   2001    4   56
1   2001    5   56
1   2001    6   56
1   2001    7   56
1   2002    3   81
1   2002    4   81
1   2002    5   81
1   2002    6   81
1   2002    7   81

…and I need the number of time that ID changes per year, so the output that I want to is:

    FisherID    Year    DiffVesselUsed
1   2000    1
1   2001    2
1   2002    0

I tried to get that using aggregate():

aggregate(vesselID, by=list(FisherID,Year,Month ), length)

but what I got was:

FisherID    Year    DiffVesselUsed
1   2000    2
1   2001    1
1   2002    1

because aggregate() counted those different vessels when those only appeared in the same month. I have tried different way to aggregate without success. Any help will be deeply appreciated. Cheers, Rafael

Answer 1

First a question: Your expected output does’t seem to reflect what you ask for. You ask for the number of times an ID changes per year, but your expected output seems to indicate that you want to know how many unique VesselIDs are observed per year. For example, in 2000, the ID changes once, and in 2001 the ID changes twice. In both years, two unique IDs are observed.

So to get the result you posted,

If you’re looking for a statistic by FisherID and Year, then there’s no reason to look by Month as well. Instead, you should look at the unique values of VesselID for each combination of FisherID and Year.

aggregate(VesselID, by = list(FisherID, Year), function(x) length(unique(x)))
#   Group.1 Group.2 x
# 1       1    2000 2
# 2       1    2001 2
# 3       1    2002 1

If you really want the number of times ID changes, use the rle function.

aggregate(VesselID, by = list(FisherID, Year),
  function(x) length(rle(x)$values) - 1)
#   Group.1 Group.2 x
# 1       1    2000 1
# 2       1    2001 2
# 3       1    2002 0