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How to find the number of numerical columns in an R data frame?
We know that a data frame can contain any type of columns such as numerical, character, logical, factor, etc. And if a data frame contains multiple type of columns then we might want to find the number of columns for each type or of one type say numerical. For this purpose, we can use select_if function of dplyr package along with the length function as shown in the below examples.
Example1
Consider the below data frame −
> x1<-letters[1:20] > x2<-rnorm(20) > x3<-rnorm(20) > x4<-rpois(20,5) > df1<-data.frame(x1,x2,x3,x4) > df1
Output
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
Loading dplyr package and finding the number of numerical columns in df1 −
> library("dplyr") > length(select_if(df1,is.numeric)) [1] 3
Example2
> 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
Output
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
Finding the number of numerical columns in df −
> length(select_if(df2,is.numeric)) [1] 3
Example3
> 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
Output
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
Finding the number of numerical columns in df3 −
> length(select_if(df3,is.numeric)) [1] 2
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