我的数据如下：
> str(tab2)
'data.frame': 36 obs. of 22 variables:
$ organisationunitname : Factor w/ 38 levels "All OUs","Angola",..: 2 3 4 5 6 7 8 9 10 11 ...
$ cd4_perform_result : num 24 6 7 1 1 1 5 3 2 1 ...
$ cd4_participate_result : num 1 8 8 1 1 1 5 3 2 1 ...
$ cd4_pass_result : num 1 4 19 1 1 1 5 3 2 1 ...
$ eid_perform_result : num 2 1 7 1 1 1 1 9 1 1 ...
$ eid_participate_result : num 2 1 5 1 1 1 1 8 1 1 ...
$ eid_pass_result : num 2 1 5 1 1 1 1 7 1 1 ...
$ vl_perform_result : num 2 1 3 1 1 1 1 9 1 1 ...
$ vl_participate_result : num 2 1 7 1 1 1 1 7 1 1 ...
$ vl_pass_result : num 2 1 7 1 1 1 1 7 1 1 ...
$ hiv_perform_result : num 19 29 14 1 1 1 26 21 10 1 ...
$ hiv_participate_result : num 19 28 14 1 1 1 22 20 4 1 ...
$ hiv_pass_result : num 20 28 14 1 1 1 18 22 7 1 ...
$ tbafb_perform_result : num 9 1 8 1 1 1 1 7 1 1 ...
$ tbafb_participate_result : num 1 1 18 1 1 1 1 5 1 1 ...
$ tbafb_pass_result : num 1 1 19 1 1 1 1 6 1 1 ...
$ tbculture_perform_result : num 3 1 2 1 1 1 1 1 1 1 ...
$ tbculture_participate_result: num 1 1 2 1 1 1 1 1 1 1 ...
$ tbculture_pass_result : num 1 1 1 1 1 1 1 1 1 1 ...
$ tbxpert_perform_result : num 1 1 4 1 1 1 1 1 1 1 ...
$ tbxpert_participate_result : num 1 1 5 1 1 1 1 1 1 1 ...
$ tbxpert_pass_result : num 1 1 2 1 1 1 1 1 1 1 ...
>
DATA
structure(list(country = c("eRkf", "KJfd", "wjkO", "Hovb", "v6Dm",
"vp8p", "TYhI", "U4OB", "GVnL", "dzJO", "11JX", "ygWc", "4Ye1",
"RykQ", "OHLW", "Xh1x", "MOl4", "67vY", "h2cA", "Ue1r", "Hr9G",
"YxpI", "S0Or", "2fss", "wz9F", "XEOG", "Vptm", "xAup", "STBG",
"AayU", "mJyW", "PvNG", "qncq", "L8dk", "6CJ8", "90i7"), cd4_perform_result = c(23,
6, 7, 1, 1, 1, 5, 3, 2, 1, 10, 1, 2, 8, 1, 2, 16, 1, 1, 22, 12,
1, 13, 11, 17, 1, 20, 15, 1, 21, 18, 4, 1, 14, 19, 9), cd4_participate_result = c(1,
8, 8, 1, 1, 1, 5, 3, 2, 1, 7, 1, 2, 9, 1, 2, 16, 1, 1, 17, 11,
1, 4, 14, 13, 1, 19, 15, 1, 20, 10, 6, 1, 18, 12, 3), cd4_pass_result = c(1,
4, 18, 1, 1, 1, 5, 3, 2, 1, 20, 1, 2, 19, 1, 2, 12, 1, 1, 13,
6, 1, 10, 11, 9, 1, 17, 2, 1, 15, 7, 16, 1, 14, 8, 3), eid_perform_result = c(2,
1, 6, 1, 1, 1, 1, 8, 1, 1, 7, 1, 2, 3, 5, 2, 5, 1, 1, 9, 5, 1,
4, 2, 10, 1, 5, 1, 1, 5, 8, 2, 1, 1, 8, 5), eid_participate_result = c(2,
1, 4, 1, 1, 1, 1, 7, 1, 1, 6, 1, 2, 9, 4, 2, 4, 1, 1, 3, 2, 1,
9, 2, 8, 1, 4, 1, 1, 4, 6, 2, 1, 1, 5, 4), eid_pass_result = c(2,
1, 4, 1, 1, 1, 1, 6, 1, 1, 5, 1, 2, 9, 1, 2, 4, 1, 1, 3, 2, 1,
8, 2, 7, 1, 4, 1, 1, 4, 5, 2, 1, 1, 4, 4), vl_perform_result = c(2,
1, 3, 1, 1, 1, 1, 8, 1, 1, 9, 1, 2, 10, 4, 2, 4, 1, 1, 5, 4,
1, 7, 6, 5, 1, 11, 1, 1, 4, 8, 2, 1, 1, 7, 4), vl_participate_result = c(2,
1, 7, 1, 1, 1, 1, 7, 1, 1, 8, 1, 2, 8, 4, 2, 4, 1, 1, 5, 2, 1,
4, 6, 3, 1, 9, 1, 1, 4, 7, 2, 1, 1, 6, 1), vl_pass_result = c(2,
1, 7, 1, 1, 1, 1, 7, 1, 1, 9, 1, 2, 8, 1, 2, 5, 1, 1, 4, 2, 1,
2, 6, 3, 1, 10, 1, 1, 5, 7, 2, 1, 1, 5, 1), hiv_perform_result = c(18,
28, 13, 1, 1, 1, 25, 20, 10, 1, 6, 11, 9, 7, 19, 26, 8, 14, 1,
27, 12, 1, 24, 17, 23, 1, 21, 5, 1, 22, 16, 15, 1, 2, 3, 4),
hiv_participate_result = c(18, 27, 13, 1, 1, 1, 21, 19, 4,
1, 15, 9, 10, 3, 11, 26, 5, 1, 1, 20, 6, 1, 23, 17, 12, 1,
24, 8, 1, 22, 14, 16, 1, 2, 25, 7), hiv_pass_result = c(19,
27, 13, 1, 1, 1, 17, 21, 6, 1, 16, 26, 10, 2, 23, 25, 9,
1, 1, 14, 4, 1, 20, 18, 11, 1, 22, 7, 1, 15, 12, 8, 1, 3,
24, 5), tbafb_perform_result = c(9, 1, 8, 1, 1, 1, 1, 7,
1, 1, 6, 1, 20, 5, 1, 2, 12, 1, 1, 15, 13, 1, 17, 11, 19,
1, 10, 1, 1, 14, 16, 4, 1, 18, 3, 1), tbafb_participate_result = c(1,
1, 17, 1, 1, 1, 1, 5, 1, 1, 12, 1, 18, 11, 1, 2, 6, 1, 1,
13, 7, 1, 10, 9, 14, 1, 8, 1, 1, 16, 15, 4, 1, 17, 3, 1),
tbafb_pass_result = c(1, 1, 18, 1, 1, 1, 1, 6, 1, 1, 13,
1, 19, 11, 1, 2, 4, 1, 1, 15, 5, 1, 7, 10, 12, 1, 8, 1, 1,
16, 9, 3, 1, 14, 17, 1), tbculture_perform_result = c(3,
1, 2, 1, 1, 1, 1, 1, 1, 1, 6, 1, 3, 8, 1, 2, 2, 1, 1, 7,
3, 1, 5, 4, 7, 1, 5, 1, 1, 3, 6, 6, 1, 3, 3, 1), tbculture_participate_result = c(1,
1, 2, 1, 1, 1, 1, 1, 1, 1, 5, 1, 3, 8, 1, 2, 2, 1, 1, 7,
2, 1, 6, 4, 6, 1, 1, 1, 1, 3, 3, 5, 1, 3, 3, 1), tbculture_pass_result = c(1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 3, 7, 1, 2, 2, 1, 1, 8,
2, 1, 6, 4, 5, 1, 1, 1, 1, 3, 3, 6, 1, 3, 3, 1), tbxpert_perform_result = c(1,
1, 4, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 16, 1, 8, 3, 1, 1, 5,
9, 1, 15, 7, 13, 1, 4, 1, 1, 12, 11, 1, 1, 6, 14, 10), tbxpert_participate_result = c(1,
1, 5, 1, 1, 1, 1, 1, 1, 1, 15, 1, 1, 4, 1, 12, 3, 1, 1, 2,
7, 1, 16, 9, 11, 1, 1, 1, 1, 14, 10, 1, 1, 6, 8, 13), tbxpert_pass_result = c(1,
1, 2, 1, 1, 1, 1, 1, 1, 1, 12, 1, 1, 4, 1, 9, 3, 1, 1, 14,
6, 1, 13, 8, 8, 1, 1, 1, 1, 11, 6, 1, 1, 5, 7, 10)), .Names = c("country",
"cd4_perform_result", "cd4_participate_result", "cd4_pass_result",
"eid_perform_result", "eid_participate_result", "eid_pass_result",
"vl_perform_result", "vl_participate_result", "vl_pass_result",
"hiv_perform_result", "hiv_participate_result", "hiv_pass_result",
"tbafb_perform_result", "tbafb_participate_result", "tbafb_pass_result",
"tbculture_perform_result", "tbculture_participate_result", "tbculture_pass_result",
"tbxpert_perform_result", "tbxpert_participate_result", "tbxpert_pass_result"
), row.names = c(NA, 36L), class = "data.frame")
它由唯一的orgnationationunitname组织，但列也分组为不同的类别。对于例如cd4，eid，vl，hiv，tbafb等然后进行表演，参与＆amp; pass_result。我想将所有这些类别的数据制成表格，如下所示
Country: eRkf
cat CD4 EID VL HIV TB AFB TB Culture TB Xpert
Perform 3442 288 114 29519 8572 72 591
Participate 1771 128 95 17342 5433 119 395
Pass_test 1535 118 83 11674 4508 109 343
如何在R中执行此操作，而无需创建单独的数据框？