dataframe - How to transform particular rows into columns in R -

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i'm new r , question might seem easy of you. have data this

> data.frame(table(dat),total)    ageintervals mytest.g_b_flag freq total 1        (1,23]               0 5718  5912 2       (23,26]               0 5249  5579 3       (26,28]               0 3105  3314 4       (28,33]               0 6277  6693 5       (33,37]               0 4443  4682 6       (37,41]               0 4277  4514 7       (41,46]               0 4904  5169 8       (46,51]               0 4582  4812 9       (51,57]               0 4039  4236 10      (57,76]               0 3926  4031 11       (1,23]               1  194  5912 12      (23,26]               1  330  5579 13      (26,28]               1  209  3314 14      (28,33]               1  416  6693 15      (33,37]               1  239  4682 16      (37,41]               1  237  4514 17      (41,46]               1  265  5169 18      (46,51]               1  230  4812 19      (51,57]               1  197  4236 20      (57,76]               1  105  4031

as might have noticed age intervals start repeating on 11 row. need 10 rows , 0's , 1' in different columns. this

ageintervals              1       0   total 1        (1,23]          194      5718  5912 2       (23,26]          330      5249  5579 3       (26,28]          209      3105  3314 4       (28,33]          416      6277  6693 5       (33,37]          239      4443  4682 6       (37,41]          237      4277  4514 7       (41,46]          265      4904  5169 8       (46,51]          230      4582  4812 9       (51,57]          197      4039  4236 10      (57,76]          105      3926  4031

many thanks

this straightforward "long" "wide" transformation easy achieve reshape base r:

reshape(mydf, idvar = c("ageintervals", "total"),          timevar = "mytest.g_b_flag", direction = "wide") #    ageintervals total freq.0 freq.1 # 1        (1,23]  5912   5718    194 # 2       (23,26]  5579   5249    330 # 3       (26,28]  3314   3105    209 # 4       (28,33]  6693   6277    416 # 5       (33,37]  4682   4443    239 # 6       (37,41]  4514   4277    237 # 7       (41,46]  5169   4904    265 # 8       (46,51]  4812   4582    230 # 9       (51,57]  4236   4039    197 # 10      (57,76]  4031   3926    105

other alternatives include:

reshape2

library(reshape2) dcast(mydf, ... ~ mytest.g_b_flag, value.var='freq')

tidyr

library(tidyr) spread(df, mytest.g_b_flag, freq)

update

this problem possibly avoidable in first place.

run following example code , compare output @ each stage:

## create sample data set.seed(1) dat <- data.frame(v1 = sample(letters[1:3], 20, true),                   v2 = sample(c(0, 1), 20, true))  ## view output dat  ## happens when use `data.frame` on `table` data.frame(table(dat))  ## compare `as.data.frame.matrix` as.data.frame.matrix(table(dat))  ## total can added automatically `addmargins` as.data.frame.matrix(addmargins(table(dat), 2, sum))

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