如何从R中的数据帧值创建字符向量?
要在R中创建字符向量,我们可以将向量值括在双引号中,但是如果要使用数据帧值创建字符向量,则可以使用as.character函数。例如,如果我们有一个数据帧df,则df中的所有值都可以使用as.character(df[])形成一个字符向量。
例1
x1<−letters[1:10] x2<−letters[11:20] df1<−data.frame(x1,x2) df1
输出结果
x1 x2 1 a k 2 b l 3 c m 4 d n 5 e o 6 f p 7 g q 8 h r 9 i s 10 j t as.character(df1[]) [1] "c(\"a\", \"b\", \"c\", \"d\", \"e\", \"f\", \"g\", \"h\", \"i\", \"j\")" [2] "c(\"k\", \"l\", \"m\", \"n\", \"o\", \"p\", \"q\", \"r\", \"s\", \"t\")" is.vector(as.character(df1[])) [1] TRUE
例2
set.seed(3232) y1<−sample(LETTERS[1:5],20,replace=TRUE) y2<−sample(LETTERS[6:15],20,replace=TRUE) y3<−sample(LETTERS[16:26],20,replace=TRUE) df2<−data.frame(y1,y2,y3) df2
输出结果
y1 y2 y3 1 E O U 2 B N U 3 C L P 4 A N Q 5 A I W 6 E M Y 7 E N P 8 B I Z 9 A G Z 10 B J W 11 D L R 12 D G R 13 B M U 14 D K W 15 B F S 16 A O Y 17 D K Z 18 A N Y 19 A O U 20 D K W as.character(df2[]) [1] "c(\"E\", \"B\", \"C\", \"A\", \"A\", \"E\", \"E\", \"B\", \"A\", \"B\", \"D\", \"D\", \"B\", \"D\", \"B\", \"A\", \"D\", \"A\", \"A\", \"D\")" [2] "c(\"O\", \"N\", \"L\", \"N\", \"I\", \"M\", \"N\", \"I\", \"G\", \"J\", \"L\", \"G\", \"M\", \"K\", \"F\", \"O\", \"K\", \"N\", \"O\", \"K\")" [3] "c(\"U\", \"U\", \"P\", \"Q\", \"W\", \"Y\", \"P\", \"Z\", \"Z\", \"W\", \"R\", \"R\", \"U\", \"W\", \"S\", \"Y\", \"Z\", \"Y\", \"U\", \"W\")" is.vector(as.character(df2[])) [1] TRUE
例子3
z1<−sample(c("Purity","Impurity","Crystal"),20,replace=TRUE)
z2<−sample(c("Chain Reaction","Odorless","Reactive"),20,replace=TRUE)
df3<−data.frame(z1,z2)
df3输出结果
z1 z2 1 Impurity Reactive 2 Crystal Reactive 3 Impurity Chain Reaction 4 Purity Chain Reaction 5 Impurity Chain Reaction 6 Crystal Reactive 7 Crystal Chain Reaction 8 Impurity Reactive 9 Purity Odorless 10 Impurity Chain Reaction 11 Purity Odorless 12 Purity Chain Reaction 13 Impurity Odorless 14 Impurity Chain Reaction 15 Impurity Odorless 16 Purity Odorless 17 Impurity Chain Reaction 18 Crystal Reactive 19 Impurity Chain Reaction 20 Crystal Reactive as.character(df3[]) [1] "c(\"Impurity\", \"Crystal\", \"Impurity\", \"Purity\", \"Impurity\", \"Crystal\", \"Crystal\", \"Impurity\", \"Purity\", \"Impurity\", \"Purity\", \"Purity\", \"Impurity\", \"Impurity\", \"Impurity\", \"Purity\", \"Impurity\", \"Crystal\", \"Impurity\", \"Crystal\")" [2] "c(\"Reactive\", \"Reactive\", \"Chain Reaction\", \"Chain Reaction\", \"Chain Reaction\", \"Reactive\", \"Chain Reaction\", \"Reactive\", \"Odorless\", \"Chain Reaction\", \"Odorless\", \"Chain Reaction\", \"Odorless\", \"Chain Reaction\", \"Odorless\", \"Odorless\", \"Chain Reaction\", \"Reactive\", \"Chain Reaction\", \"Reactive\")" is.vector(as.character(df3[])) [1] TRUE
热门推荐
10 香港老妈结婚祝福语简短
11 毕业立体贺卡祝福语简短
12 简短新年年会祝福语
13 评论小品祝福语大全简短
14 恭喜师兄结婚祝福语简短
15 员工集体辞职祝福语简短
16 高中新生祝福语 简短
17 装修祝福语男生搞笑简短
18 生日开业蛋糕祝福语简短