r - Frequency table including zeros for unused values, on a data.table -


i have data set follows:

library(data.table)  test <- data.table(structure(list(issue.date = structure(c(16041, 16056, 16042,15990, 15996, 16001, 15995, 15981, 15986, 15996, 15996, 16002,16015, 16020, 16025, 16032, 16023, 16084, 16077, 16102, 16104,16107, 16112, 16113, 16115, 16121, 16125, 16128, 16104, 16132,16133, 16135, 16139, 16146, 16151), class = "date"),      complaint = structure(c(1l,4l, 4l, 4l, 4l, 4l, 4l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 1l,5l, 3l, 1l, 3l, 1l, 4l, 4l, 3l, 3l, 3l, 3l, 3l, 2l, 2l, 1l, 3l,3l, 3l), .label = c("a", "b", "c", "d", "e"), class = "factor"),     yr = c("2013", "2013", "2013", "2013", "2013", "2013", "2013","2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013","2013", "2013", "2014", "2014", "2014", "2014", "2014", "2014","2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014","2014", "2014", "2014", "2014"),      month = c("2013-12", "2013-12","2013-12", "2013-10", "2013-10", "2013-10", "2013-10", "2013-10","2013-10", "2013-10", "2013-10", "2013-10", "2013-11", "2013-11","2013-11", "2013-11", "2013-11", "2014-01", "2014-01", "2014-02","2014-02", "2014-02", "2014-02", "2014-02", "2014-02", "2014-02","2014-02", "2014-02", "2014-02", "2014-03", "2014-03", "2014-03","2014-03", "2014-03", "2014-03"),      da = c("02", "17", "03","12", "18", "23", "17", "03", "08", "18", "18", "24", "06","11", "16", "23", "14", "14", "07", "01", "03", "06", "11","12", "14", "20", "24", "27", "03", "03", "04", "06", "10","17", "22")),     .names = c("issue.date", "complaint", "yr","month", "da"), class = c("data.table", "data.frame"), row.names = c(na,-35l)))

basically use data.table create frequency table has complaint , count month. trick need show count of 0 if there no complaints of type month. know how without showing zeros, want know how include them.

test[ , count := .n, = "month,complaint"]

to directly counts each group:

setkey(test, month, complaint)  # may need add allow.cartesian, depending on actual data test[cj(month, complaint, unique = true), .n, = .eachi] #      month complaint n # 1: 2013-10         0 # 2: 2013-10         b 0 # 3: 2013-10         c 5 # 4: 2013-10         d 4 # 5: 2013-10         e 0 # 6: 2013-11         1 # 7: 2013-11         b 0 # 8: 2013-11         c 4 # 9: 2013-11         d 0 #10: 2013-11         e 0 #11: 2013-12         1 #12: 2013-12         b 0 #13: 2013-12         c 0 #14: 2013-12         d 2 #15: 2013-12         e 0 #16: 2014-01         0 #17: 2014-01         b 0 #18: 2014-01         c 1 #19: 2014-01         d 0 #20: 2014-01         e 1 #21: 2014-02         2 #22: 2014-02         b 0 #23: 2014-02         c 6 #24: 2014-02         d 2 #25: 2014-02         e 0 #26: 2014-03         1 #27: 2014-03         b 2 #28: 2014-03         c 3 #29: 2014-03         d 0 #30: 2014-03         e 0 #      month complaint n

see first revision of answer if want have counts in full data.table instead of summarizing.


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