all.equal could have option to sub-aggregate before comparison
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Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 45/100
Research direction
Start by reading the data.table implementation and documentation for all.equal, then inspect its existing comparison behavior and tests. Define how the by and fun.aggregate options should work for differing granularities, using the supplied d1 and d2 example as the acceptance case. Done means the example returns TRUE without manual aggregation and existing all.equal behavior remains unchanged.
Written by the indexing model from the issue text.
Description
It is very common operation to compare data which could have been sub-aggregated to different levels of granularity. When we align their level of granularity, then data happens to be equal. We could provide easy way to do that without user having to manually sub-aggregate each data each time.
Expected behavior:
d1 = data.table(a = 1:2, b=c(1,2))
d2 = data.table(a = c(1:2,2L), b=c(1,1,1))
d1
# a b
# <int> <num>
#1: 1 1
#2: 2 2
d2
# a b
# <int> <num>
#1: 1 1
#2: 2 1
#3: 2 1
all.equal(d1, d2, by = "a") # default: fun.aggregate=sum
# [1] TRUE
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