我有一个如下所示的表格(数据发布在下面):
我想排除所有 iso3c (三个字母代码)其中 var没有至少三个值(即 0、1、2、3)。例如，对于 AGO唯一的值是 0 。所以这个需要走。下一篇ALB可以保留，因为该值上升到 3 。我想做类似的事情，setDT(DT)[max(as.numeric(as.character(var))) <3, iso3c:=NA, by="iso3c"] 。但这对数据没有任何影响。
有什么想法吗？
table(DT)
var AGO ALB ARG ARM AZE BDI BEN BFA BGR BiH BLR BOL BRA BWA CHL CHN CMR COD COL CPV CRI Czech DEU DOM ECU ESP EST GEO GIN GMB GRC GTM GUY HND HRV HUN IDN IND IRL JAM JOR
0 10 4 10 8 7 9 3 9 2 5 7 9 3 8 9 1 10 10 10 9 5 3 7 3 8 6 6 2 10 10 5 9 6 8 6 8 6 7 6 1 10
1 0 3 0 2 3 1 2 1 2 3 3 1 1 2 0 3 0 0 0 1 1 3 2 0 0 0 2 2 0 0 5 0 0 1 3 1 1 2 2 0 0
2 0 1 0 0 0 0 2 0 3 2 0 0 2 0 1 4 0 0 0 0 2 3 0 1 0 3 2 2 0 0 0 0 2 0 0 0 0 0 0 4 0
3 0 2 0 0 0 0 2 0 2 0 0 0 2 0 0 2 0 0 0 0 0 1 1 5 0 1 0 4 0 0 0 0 2 0 1 1 2 0 2 2 0
4 0 0 0 0 0 0 1 0 1 0 0 0 2 0 0 0 0 0 0 0 2 0 0 1 2 0 0 0 0 0 0 1 0 1 0 0 1 1 0 3 0
iso3c
var KAZ KEN KGZ KHM KOR LAO LBN LKA LSO LTU LVA MAR MDA MDG MEX MKD MLI MNE MNG MRT MUS MWI NAM NIC PAN PER PHL POL PRT PRY PSE ROU RUS SEN Serbia&Montenegro SLV SRB SVK
0 10 1 2 2 8 2 4 5 0 3 4 7 4 1 9 3 4 2 4 9 5 0 5 10 10 7 7 6 4 9 10 4 2 4 3 8 3 7
1 0 0 4 2 2 4 2 3 1 4 1 0 3 2 1 3 1 1 2 1 1 0 5 0 0 2 0 3 2 1 0 3 3 5 4 2 3 2
2 0 1 1 2 0 3 1 1 3 3 4 1 3 5 0 2 2 4 1 0 1 1 0 0 0 0 1 0 2 0 0 2 5 1 1 0 2 0
3 0 4 3 3 0 1 2 1 3 0 1 0 0 2 0 2 1 2 2 0 3 2 0 0 0 1 2 1 2 0 0 1 0 0 2 0 1 1
4 0 4 0 1 0 0 1 0 3 0 0 2 0 0 0 0 2 1 1 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
iso3c
var SVN SWZ TJK TUR TZA UGA UKR URY UZB VNM ZAF ZMB
0 7 10 6 2 7 9 5 10 7 6 2 0
1 0 0 3 3 2 1 1 0 3 3 2 4
2 2 0 1 3 0 0 3 0 0 1 2 1
3 1 0 0 0 1 0 1 0 0 0 1 3
4 0 0 0 2 0 0 0 0 0 0 3 2
数据
DT <- structure(list(var= structure(c(2, 0, 0, 3, 4,
4, 1, 0, 2, 3, 1, 2, 3, 4, 2, 3, 3, 0, 0, 1, 3, 2, 3, 2, 2, 0,
2, 1, 1, 1, 4, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0,
0, 4, 0, 0, 1, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 1, 0, 3, 4, 3,
0, 0, 3, 4, 3, 4, 0, 4, 4, 3, 3, 2, 0, 2, 0, 2, 3, 2, 3, 1, 2,
4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 3, 0,
0, 0, 3, 0, 0, 0, 2, 3, 0, 0, 1, 2, 0, 4, 2, 1, 0, 1, 3, 0, 0,
1, 1, 0, 2, 0, 1, 0, 3, 0, 0, 0, 3, 0, 1, 0, 0, 1, 0, 0, 3, 1,
1, 4, 1, 2, 3, 1, 4, 3, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 4, 2,
1, 1, 4, 3, 2, 0, 4, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 3, 2, 0,
0, 0, 2, 0, 0, 3, 1, 0, 2, 1, 1, 0, 1, 1, 0, 0, 0, 4, 0, 3, 0,
1, 2, 4, 2, 0, 1, 0, 0, 2, 0, 0, 0, 0, 1, 1, 3, 0, 2, 3, 0, 0,
3, 1, 0, 0, 2, 4, 0, 4, 0, 0, 0, 0, 0, 0, 2, 2, 2, 0, 2, 3, 3,
1, 1, 2, 3, 3, 3, 1, 1, 1, 1, 0, 0, 2, 4, 4, 3, 4, 3, 2, 4, 4,
4, 4, 3, 3, 1, 4, 2, 0, 2, 1, 0, 0, 1, 0, 2, 0, 1, 0, 0, 2, 3,
3, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 3, 0, 0, 1, 3, 0, 1, 4, 2, 0,
0, 0, 1, 4, 0, 0, 0, 2, 2, 4, 4, 0, 3, 1, 1, 0, 3, 0, 0, 2, 1,
3, 4, 3, 2, 2, 4, 4, 3, 2, 3, 4, 3, 4, 0, 4, 2, 2, 2, 2, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1,
0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 4, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 0,
0, 0, 3, 3, 2, 3, 4, 3, 1, 1, 0, 2, 0, 3, 1, 0, 2, 0, 0, 3, 1,
2, 1, 1, 3, 0, 0, 0, 1, 0, 0, 1, 1, 3, 0, 0, 0, 2, 1, 0, 1, 2,
0, 0, 1, 0, 0, 0, 0, 2, 0, 0, 0, 0, 2, 3, 0, 1, 0, 1, 3, 1, 3,
1, 0, 2, 0, 1, 0, 2, 1, 4, 4, 1, 2, 0, 2, 0, 1, 0, 0, 0, 0, 0,
1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 3, 0, 3, 0, 0, 1, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 3, 0, 3, 0, 0, 2, 2, 1, 0, 1, 1,
2, 1, 0, 0, 2, 1, 2, 1, 2, 0, 0, 0, 1, 2, 0, 2, 1, 3, 1, 0, 0,
2, 1, 3, 1, 0, 2, 2, 0, 4, 3, 3, 0, 2, 2, 0, 1, 2, 0, 0, 2, 0,
0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0,
2, 0, 0, 0, 2, 1, 0, 0, 3, 3, 0, 3, 2, 0, 1, 1, 2, 3, 2, 1, 1,
0, 2, 1, 0, 1, 0, 2, 2, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 2, 1, 0, 1, 2,
1, 0, 2, 2, 2, 0, 0, 2, 2, 1, 0, 2, 0, 0, 3, 2, 2, 0, 0, 0, 0,
2, 3, 0, 0, 1, 0, 0, 1, 0, 3, 3, 0, 0, 0, 0, 0, 3, 0, 0, 1, 0,
0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 2, 0, 1, 2, 1, 3,
0, 2), label = "label", format.stata = "%20.0f", class = c("haven_labelled",
"vctrs_vctr", "double"), labels = c(`No obstacle` = 0, `Minor obstacle` = 1,
`Moderate obstacle` = 2, `Major obstacle` = 3, `Very Severe Obstacle` = 4
)), iso3c = structure(c(13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 32L, 32L, 32L, 32L, 32L, 32L, 32L,
32L, 32L, 32L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L,
37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 43L, 43L, 43L,
43L, 43L, 43L, 43L, 43L, 43L, 43L, 59L, 59L, 59L, 59L, 59L, 59L,
59L, 59L, 59L, 59L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L,
65L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 68L, 68L,
68L, 68L, 68L, 68L, 68L, 68L, 68L, 68L, 78L, 78L, 78L, 78L, 78L,
78L, 78L, 78L, 78L, 78L, 49L, 49L, 49L, 49L, 49L, 49L, 49L, 49L,
49L, 49L, 84L, 84L, 84L, 84L, 84L, 84L, 84L, 84L, 84L, 84L, 91L,
91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 77L, 77L, 77L, 77L,
77L, 77L, 77L, 77L, 77L, 77L, 90L, 90L, 90L, 90L, 90L, 90L, 90L,
90L, 90L, 90L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
33L, 33L, 33L, 33L, 33L, 33L, 33L, 33L, 33L, 33L, 75L, 75L, 75L,
75L, 75L, 75L, 75L, 75L, 75L, 75L, 58L, 58L, 58L, 58L, 58L, 58L,
58L, 58L, 58L, 58L, 89L, 89L, 89L, 89L, 89L, 89L, 89L, 89L, 89L,
89L, 62L, 62L, 62L, 62L, 62L, 62L, 62L, 62L, 62L, 62L, 53L, 53L,
53L, 53L, 53L, 53L, 53L, 53L, 53L, 53L, 55L, 55L, 55L, 55L, 55L,
55L, 55L, 55L, 55L, 55L, 44L, 44L, 44L, 44L, 44L, 44L, 44L, 44L,
44L, 44L, 63L, 63L, 63L, 63L, 63L, 63L, 63L, 63L, 63L, 63L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 70L, 70L, 70L, 70L, 70L,
70L, 70L, 70L, 70L, 70L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L,
31L, 31L, 48L, 48L, 48L, 48L, 48L, 48L, 48L, 48L, 48L, 48L, 21L,
21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 60L, 60L, 60L, 60L,
60L, 60L, 60L, 60L, 60L, 60L, 50L, 50L, 50L, 50L, 50L, 50L, 50L,
50L, 50L, 50L, 40L, 40L, 40L, 40L, 40L, 40L, 40L, 40L, 40L, 40L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 18L, 18L, 18L, 18L, 18L, 18L, 18L,
18L, 18L, 18L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
61L, 61L, 61L, 61L, 61L, 61L, 61L, 61L, 61L, 61L, 85L, 85L, 85L,
85L, 85L, 85L, 85L, 85L, 85L, 85L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L,
64L, 81L, 81L, 81L, 81L, 81L, 81L, 81L, 81L, 81L, 81L, 29L, 29L,
29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 56L, 56L,
56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 66L, 66L, 66L, 66L, 66L,
66L, 66L, 66L, 66L, 66L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L,
87L, 87L, 71L, 71L, 71L, 71L, 71L, 71L, 71L, 71L, 71L, 71L, 38L,
38L, 38L, 38L, 38L, 38L, 38L, 38L, 38L, 38L, 72L, 72L, 72L, 72L,
72L, 72L, 72L, 72L, 72L, 72L, 41L, 41L, 41L, 41L, 41L, 41L, 41L,
41L, 41L, 41L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L,
57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 35L, 35L, 35L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 76L, 76L, 76L,
76L, 76L, 76L, 76L, 76L, 76L, 76L, 83L, 83L, 83L, 83L, 83L, 83L,
83L, 83L, 83L, 83L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 36L, 36L,
36L, 36L, 36L, 36L, 36L, 36L, 36L, 36L, 79L, 79L, 79L, 79L, 79L,
79L, 79L, 79L, 79L, 79L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L,
22L, 22L, 54L, 54L, 54L, 54L, 54L, 54L, 54L, 54L, 54L, 54L, 73L,
73L, 73L, 73L, 73L, 73L, 73L, 73L, 73L, 73L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L,
52L, 52L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 27L, 27L, 27L, 27L, 27L, 27L, 27L,
27L, 27L, 27L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L,
51L, 51L, 51L, 51L, 51L, 51L, 51L, 51L, 51L, 51L, 82L, 82L, 82L,
82L, 82L, 82L, 82L, 82L, 82L, 82L, 42L, 42L, 42L, 42L, 42L, 42L,
42L, 42L, 42L, 42L, 88L, 88L, 88L, 88L, 88L, 88L, 88L, 88L, 88L,
88L, 74L, 74L, 74L, 74L, 74L, 74L, 74L, 74L, 74L, 74L, 86L, 86L,
86L, 86L, 86L, 86L, 86L, 86L, 86L, 86L, 26L, 26L, 26L, 26L, 26L,
26L, 26L, 26L, 26L, 26L, 39L, 39L, 39L, 39L, 39L, 39L, 39L, 39L,
39L, 39L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 46L,
46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 47L, 47L, 47L, 47L,
47L, 47L, 47L, 47L, 47L, 47L), .Label = c("AGO", "ALB", "ARG",
"ARM", "AZE", "BDI", "BEN", "BFA", "BGR", "BiH", "BLR", "BOL",
"BRA", "BWA", "CHL", "CHN", "CMR", "COD", "COL", "CPV", "CRI",
"Czech", "DEU", "DOM", "ECU", "ESP", "EST", "GEO", "GIN", "GMB",
"GRC", "GTM", "GUY", "HND", "HRV", "HUN", "IDN", "IND", "IRL",
"JAM", "JOR", "KAZ", "KEN", "KGZ", "KHM", "KOR", "LAO", "LBN",
"LKA", "LSO", "LTU", "LVA", "MAR", "MDA", "MDG", "MEX", "MKD",
"MLI", "MNE", "MNG", "MRT", "MUS", "MWI", "NAM", "NIC", "PAN",
"PER", "PHL", "POL", "PRT", "PRY", "PSE", "ROU", "RUS", "SEN",
"Serbia&Montenegro", "SLV", "SRB", "SVK", "SVN", "SWZ", "TJK",
"TUR", "TZA", "UGA", "UKR", "URY", "UZB", "VNM", "ZAF", "ZMB"
), class = "factor")), row.names = c(NA, -910L), class = c("data.table",
"data.frame"))
最佳答案
按“iso3c”分组，获取“var”中唯一元素的计数，从中创建一个逻辑向量，获取行索引 (.I) 和基于该列的子集
DT1 <- droplevels(DT[DT[, .I[uniqueN(var) >=3],iso3c]$V1])
关于r - 按组消除不存在某些因子值的行，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/66785543/