如何从R数据帧中仅选择一列并将其作为数据帧而不是向量返回？
通常，如果我们从R数据帧中提取单个列，则将其提取为向量，但我们可能希望以数据帧形式来使用它，以便可以在其上应用数据帧的操作。因此，我们可以使用单个方括号来提取具有T(TRUE)或(FALSE)值和drop=FALSE的值，以便输出成为数据帧。
请看以下数据帧-
示例
set.seed(999) x1<-rnorm(20,5,1) x2<-rnorm(20,5,2) x3<-rnorm(20,10,2) x4<-rnorm(20,10,1.5) x5<-rnorm(20,10,4) df1<-data.frame(x1,x2,x3,x4,x5) df1
输出结果
x1 x2 x3 x4 x5 1 4.718260 2.542873 9.028727 8.615033 7.428309 2 3.687440 6.286089 10.016996 11.747431 13.941194 3 5.795184 4.280474 7.435773 11.563103 5.085707 4 5.270070 5.588071 7.776842 11.655743 10.340899 5 4.722694 2.749463 10.601331 9.972138 5.183625 6 4.433976 6.284531 10.552958 8.279563 8.492609 7 3.121342 2.786525 5.898245 7.887731 15.454594 8 3.733209 3.230319 10.028380 9.576507 8.988469 9 4.032250 1.891810 11.164533 9.373345 14.025960 10 3.878991 4.746642 9.930547 11.494995 11.748597 11 6.325464 9.765328 9.766672 9.840571 16.634154 12 5.133977 6.202552 8.710036 9.895897 10.110741 13 5.938749 5.358723 13.488823 11.424552 6.085122 14 5.172538 7.161063 10.732189 9.375201 15.134917 15 5.957650 4.506376 9.866380 11.461001 5.481034 16 3.637314 0.772526 10.565225 10.093437 14.186631 17 5.068335 4.258945 11.135390 10.807633 7.688271 18 5.100658 6.045736 7.441568 6.902765 8.824823 19 5.901345 6.035611 10.870738 10.654647 9.032894 20 2.925643 2.194978 8.868998 9.759660 10.879791
提取列x1-
df1[，c(T,F,F,F,F)]
[1] 4.718260 3.687440 5.795184 5.270070 4.722694 4.433976 3.121342 3.733209 [9] 4.032250 3.878991 6.325464 5.133977 5.938749 5.172538 5.957650 3.637314 [17] 5.068335 5.100658 5.901345 2.925643
is.vector（df1[，c(T,F,F,F,F)]）[1]是
提取列x1作为数据帧-
df1[，c(T,F,F,F,F)，drop=FALSE]
x1 1 4.718260 2 3.687440 3 5.795184 4 5.270070 5 4.722694 6 4.433976 7 3.121342 8 3.733209 9 4.032250 10 3.878991 11 6.325464 12 5.133977 13 5.938749 14 5.172538 15 5.957650 16 3.637314 17 5.068335 18 5.100658 19 5.901345 20 2.925643
以相同的方式提取不同的列-
df1[，c(F,T,F,F,F)，drop=FALSE]
x2 1 2.542873 2 6.286089 3 4.280474 4 5.588071 5 2.749463 6 6.284531 7 2.786525 8 3.230319 9 1.891810 10 4.746642 11 9.765328 12 6.202552 13 5.358723 14 7.161063 15 4.506376 16 0.772526 17 4.258945 18 6.045736 19 6.035611 20 2.194978
df1[，c(F,F,T,F,F)，drop=FALSE]
x3 1 9.028727 2 10.016996 3 7.435773 4 7.776842 5 10.601331 6 10.552958 7 5.898245 8 10.028380 9 11.164533 10 9.930547 11 9.766672 12 8.710036 13 13.488823 14 10.732189 15 9.866380 16 10.565225 17 11.135390 18 7.441568 19 10.870738 20 8.868998
df1[，c(F,F,F,F,T)，drop=FALSE]
x5 1 7.428309 2 13.941194 3 5.085707 4 10.340899 5 5.183625 6 8.492609 7 15.454594 8 8.988469 9 14.025960 10 11.748597 11 16.634154 12 10.110741 13 6.085122 14 15.134917 15 5.481034 16 14.186631 17 7.688271 18 8.824823 19 9.032894 20 10.879791