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法律研究如何在 R 中從資料框值建立字元向量？
要建立 R 中的字元向量，我們可以將向量值置於雙引號中，但如果我們想要使用資料框值來建立字元向量，就可以使用 as.character 函式。例如，如果我們有一個數據框 df，那麼 df 中的所有值都可以使用 as.character(df[]) 形成一個字元向量。
範例 1
x1<−letters[1:10] x2<−letters[11:20] df1<−data.frame(x1,x2) df1
輸出
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
範例 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
輸出
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
範例 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輸出
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
更新時間： 2020 年 11 月 7 日
3K+ 次瀏覽
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