如何找到R数据框中的数字列数？
我们知道数据框可以包含任何类型的列，例如数字，字符，逻辑，因子等。并且，如果数据框包含多种类型的列，则我们可能希望查找每种类型或一个类型的列数输入数字。为此，我们可以将dplyr包的select_if函数与length函数一起使用，如以下示例所示。
例1
考虑以下数据帧-
> x1<-letters[1:20] > x2<-rnorm(20) > x3<-rnorm(20) > x4<-rpois(20,5) > df1<-data.frame(x1,x2,x3,x4) > df1输出结果
x1 x2 x3 x4 1 a -0.18404831 0.1082741 2 2 b -0.28597330 0.2584625 0 3 c 1.29158108 -0.5444644 6 4 d -0.80355312 -0.2261304 3 5 e -0.86895219 -0.9499907 4 6 f -0.69489165 0.4523057 3 7 g 0.70987445 -0.1152756 6 8 h 1.46023245 -1.5871850 8 9 i -0.14756283 0.4843958 4 10 j -1.46142329 0.7888207 12 11 k -0.20521299 -0.6228141 9 12 l 0.76613077 -1.3652169 9 13 m 0.07624931 0.3870339 5 14 n 1.22399304 0.4028503 3 15 o -0.09727281 -0.5263696 8 16 p -1.97470094 -0.1248541 4 17 q 0.11621840 -1.9126845 4 18 r -1.13008040 -1.5671634 1 19 s 0.73929690 -0.2571851 3 20 t -0.13389093 0.4876529 4
加载dplyr软件包并找到df1中的数字列数-
> library("dplyr")
> length(select_if(df1,is.numeric))
[1] 3例2
> y1<-LETTERS[1:20]
> y2<-rpois(20,2)
> y3<-rpois(20,2)
> y4<-rpois(20,10)
> y5<-sample(c("Hot","Cold"),20,replace=TRUE)
> df2<-data.frame(y1,y2,y3,y4,y5)
> df2输出结果y1 y2 y3 y4 y5 1 A 1 1 10 Cold 2 B 2 0 24 Hot 3 C 3 0 13 Cold 4 D 1 3 14 Cold 5 E 4 4 16 Hot 6 F 3 3 9 Cold 7 G 2 2 12 Hot 8 H 3 1 6 Hot 9 I 4 0 11 Hot 10 J 2 1 14 Hot 11 K 2 0 14 Hot 12 L 1 1 8 Hot 13 M 3 2 10 Hot 14 N 0 5 9 Cold 15 O 1 2 14 Hot 16 P 1 0 13 Cold 17 Q 7 2 13 Hot 18 R 1 2 4 Cold 19 S 1 1 7 Cold 20 T 3 3 10 Hot
在df中找到数字列的数量-
> length(select_if(df2,is.numeric)) [1] 3
范例3
> z1<-sample(c("Male","Female"),20,replace=TRUE)
> z2<-rpois(20,25)
> z3<-rnorm(20,2,0.3)
> df3<-data.frame(z1,z2,z3)
> df3输出结果z1 z2 z3 1 Female 20 2.037433 2 Female 36 2.252606 3 Female 28 2.126866 4 Male 30 1.966581 5 Male 20 1.871318 6 Female 26 2.250764 7 Male 29 1.882002 8 Female 21 1.796225 9 Male 21 2.404416 10 Male 25 1.571489 11 Female 18 2.419949 12 Male 24 1.974340 13 Male 34 1.877119 14 Male 30 2.390536 15 Female 21 1.688357 16 Female 25 1.664844 17 Male 22 2.060667 18 Male 26 1.391200 19 Female 23 1.757949 20 Female 24 1.727739
在df3中找到数字列的数量-
> length(select_if(df3,is.numeric)) [1] 2