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bug in group_by #1093

@sfischme

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@sfischme

Try this:

            time type loc                             call     p cnt
1  1304945116000    a   b 1fb646244dbd6c807005811838b1e5ec 53115   0
2  1304945116000    a   b 6b3dafa1ff257c3891fc87abc78e137e     1   0
3  1304945116000    a   b 6e6f8c68c86173aa7e98b6375e752f89    NA   0
4  1304945116000    a   b d02922f7a545c15632c9ecb39e6da9a2    NA   0
5  1304945116000    a   b 11ce203ca480e56f03a7d1a9591de0e9    NA   0
6  1304945116000    a   b 7dabc9db21bbdc080780f493fe93f2af 53115   0
7  1304945116001    a   b 6b3dafa1ff257c3891fc87abc78e137e     1   1
8  1304945116001    a   b 6e6f8c68c86173aa7e98b6375e752f89    NA   1
9  1304945116001    a   b d02922f7a545c15632c9ecb39e6da9a2    NA   1
10 1304945116001    a   b 11ce203ca480e56f03a7d1a9591de0e9    NA   1

# now compare these two, they should be the same:
q.2 %>% group_by(time, type, loc, call) %>% summarize(n=n()) %>% filter(n>1)
q.2 %>% data.table() %>% group_by(time, type, loc, call) %>% summarize(n=n()) %>% filter(n>1)

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