如果R中两个向量的字符串大小写不同，如何匹配两个字符串向量？
我们知道，R是区分大小写的编程语言，因此匹配不同大小写的字符串并不简单。例如，如果一个向量包含tutorialspoint，另一个向量包含TUTORIALSPOINT，则要检查字符串是否匹配，我们不能直接使用match函数。为此，我们必须使用match函数将小写字符串转换为大写或将大写转换为小写。
例子
> x1<-sample(letters[1:26],100,replace=TRUE) > x1
输出结果
[1] "z" "v" "r" "y" "z" "l" "v" "t" "f" "p" "p" "z" "e" "b" "a" "o" "m" "d" [19] "e" "l" "y" "y" "u" "u" "w" "b" "a" "j" "n" "v" "b" "q" "b" "d" "l" "a" [37] "g" "g" "g" "o" "k" "r" "q" "e" "x" "i" "r" "l" "b" "r" "j" "k" "b" "f" [55] "r" "f" "r" "n" "y" "y" "l" "k" "y" "s" "b" "a" "s" "f" "a" "l" "j" "i" [73] "q" "o" "t" "v" "t" "r" "i" "x" "s" "q" "h" "t" "y" "k" "a" "h" "e" "m" [91] "u" "d" "q" "i" "h" "x" "k" "j" "p" "h"
示例
> x2<-sample(LETTERS[1:10],100,replace=TRUE) > x2
输出结果
[1] "E" "C" "F" "F" "A" "H" "E" "F" "D" "F" "J" "G" "G" "D" "E" "G" "G" "F" [19] "A" "C" "C" "H" "E" "G" "H" "A" "B" "A" "H" "G" "D" "J" "G" "C" "D" "I" [37] "F" "B" "D" "D" "C" "D" "E" "D" "B" "E" "E" "H" "D" "D" "I" "B" "I" "J" [55] "C" "C" "H" "D" "B" "D" "F" "F" "D" "F" "E" "B" "F" "J" "D" "B" "G" "J" [73] "G" "C" "E" "A" "I" "B" "D" "A" "G" "G" "F" "D" "E" "E" "G" "I" "D" "D" [91] "I" "E" "J" "D" "E" "B" "C" "A" "I" "C"
> match(x1,tolower(x2))
输出结果
[1] NA NA NA NA NA NA NA NA 3 NA NA NA 1 27 5 NA NA 9 1 NA NA NA NA NA NA [26] 27 5 11 NA NA 27 NA 27 9 NA 5 12 12 12 NA NA NA NA 1 NA 36 NA NA 27 NA [51] 11 NA 27 3 NA 3 NA NA NA NA NA NA NA NA 27 5 NA 3 5 NA 11 36 NA NA NA [76] NA NA NA 36 NA NA NA 6 NA NA NA 5 6 1 NA NA 9 NA 36 6 NA NA 11 NA 6
> x3<-c("AK", "AL", "AR", "AS", "AZ", "CA", "CO", "CT", "DC", "DE", "FL", "GA",
"GU", "HI", "IA", "ID", "IL", "IN", "KS", "KY", "LA", "MA", "MD", "ME", "MI",
"MN", "MO", "MP", "MS", "MT", "NC", "ND", "NE", "NH", "NJ", "NM", "NV", "NY",
"OH", "OK", "OR", "PA", "PR", "RI", "SC", "SD", "TN", "TX", "UM", "UT", "VA",
"VI", "VT", "WA", "WI", "WV", "WY")
> x3
[1] "AK" "AL" "AR" "AS" "AZ" "CA" "CO" "CT" "DC" "DE" "FL" "GA" "GU" "HI"
"IA"
[16] "ID" "IL" "IN" "KS" "KY" "LA" "MA" "MD" "ME" "MI" "MN" "MO" "MP" "MS"
"MT"
[31] "NC" "ND" "NE" "NH" "NJ" "NM" "NV" "NY" "OH" "OK" "OR" "PA" "PR" "RI"
"SC"
[46] "SD" "TN" "TX" "UM" "UT" "VA" "VI" "VT" "WA" "WI" "WV" "WY"> x4<-c("ak", "al", "ar", "as", "az", "ca", "co", "ct", "dc", "de", "fl", "ga", "gu", "hi", "ia",
"id", "il", "in", "ks", "ky", "la", "ma", "md", "me", "mi", "mn", "mo", "mp", "ms", "mt",
"nc", "nd", "ne", "nh", "nj", "nm", "nv", "ny", "oh", "ok", "or", "pa", "pr", "ri", "sc", "sd",
"tn", "tx", "um", "ut", "va", "vi", "vt", "wa", "wi", "wv", "wy")
> x4
[1] "ak" "al" "ar" "as" "az" "ca" "co" "ct" "dc" "de" "fl" "ga" "gu" "hi" "ia"
[16] "id" "il" "in" "ks" "ky" "la" "ma" "md" "me" "mi" "mn" "mo" "mp" "ms" "mt"
[31] "nc" "nd" "ne" "nh" "nj" "nm" "nv" "ny" "oh" "ok" "or" "pa" "pr" "ri" "sc"
[46] "sd" "tn" "tx" "um" "ut" "va" "vi" "vt" "wa" "wi" "wv" "wy"
> length(x4)
[1] 57
> length(x3)
[1] 57> match(x3,toupper(x4))
输出结果
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 [26] 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 [51] 51 52 53 54 55 56 57
> match(LETTERS[1:20],toupper(c(letters[1:26])))
输出结果
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
> match(LETTERS[1:20],toupper(c(letters[1:10])))
输出结果
[1] 1 2 3 4 5 6 7 8 9 10 NA NA NA NA NA NA NA NA NA NA
> match(LETTERS[10:1],toupper(c(letters[1:10])))
输出结果
[1] 10 9 8 7 6 5 4 3 2 1
> match(sample(LETTERS[10:1],50,replace=TRUE),toupper(c(letters[1:10])))
输出结果
[1] 2 10 8 7 10 8 4 8 2 7 10 3 5 5 4 6 4 10 7 3 7 1 1 3 10 [26] 3 7 4 3 7 5 4 5 2 7 4 5 1 5 7 2 4 4 2 8 8 9 5 1 2
> match(sample(letters[26:1],50,replace=TRUE),tolower(c(LETTERS[1:20])))
输出结果
[1] 8 2 18 15 15 14 11 13 18 5 9 13 14 20 18 15 4 14 5 NA NA 5 NA 8 17 [26] 5 16 3 4 9 NA 5 16 17 16 6 12 1 2 NA NA 8 16 9 NA 14 NA 11 16 15
> match(sample(c("india","russia","china","uk"),50,replace=TRUE),tolower(c("INDIA","R
USSIA","CHINA")))输出结果
[1] NA 3 2 1 3 1 NA NA NA 2 NA 3 3 3 1 NA NA 3 3 3 2 3 2 3 2 [26] 3 3 NA 3 3 2 NA 3 1 NA 3 NA 3 1 NA 3 NA NA NA NA 3 NA 2 NA NA