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How to find the groupwise number of positive and negative values in an R data frame?
To find the groupwise number of positive and negative values in an R data frame, we can use mutate function of dplyr package. For example, if we have a data frame called df with one categorical column x and one numerical column y then the number of positive and negative values for categorical column can be found by using the below command −
df%>%group_by(x)%>%mutate(positive=sum(y>0),negative=sum(y<0))
Consider the below data frame −
Example
Group<-sample(LETTERS[1:4],20,replace=TRUE) y1<-rnorm(20) df1<-data.frame(Group,y1) df1
Output
Group y1 1 C 0.85135509 2 D -1.65551392 3 C -3.02201905 4 B -0.89625797 5 A 0.28129292 6 A -0.04801872 7 D -0.95801637 8 B 1.42274072 9 A -1.18959023 10 A 0.60031795 11 C 0.22474189 12 B 2.17627556 13 D 1.24592142 14 A -0.46659749 15 B 0.43163726 16 D -0.95450596 17 C 2.89909436 18 D 0.55951749 19 C -0.48761069 20 B 0.85106755
Loading dplyr package and finding groupwise number of positive and negative values for Group column in df1 −
Example
library(dplyr) df1%>%group_by(Group)%>%mutate(positive=sum(y1>0),negative=sum(y1<0))
A tibble: 20 x 4
Groups: Group [4]
Output
Group y1 positive negative <chr> <dbl> <int> <int> 1 C 0.851 3 2 2 D -1.66 2 3 3 C -3.02 3 2 4 B -0.896 4 1 5 A 0.281 2 3 6 A -0.0480 2 3 7 D -0.958 2 3 8 B 1.42 4 1 9 A -1.19 2 3 10 A 0.600 2 3 11 C 0.225 3 2 12 B 2.18 4 1 13 D 1.25 2 3 14 A -0.467 2 3 15 B 0.432 4 1 16 D -0.955 2 3 17 C 2.90 3 2 18 D 0.560 2 3 19 C -0.488 3 2 20 B 0.851 4 1
Example
Class<-sample(c("Male","Female"),20,replace=TRUE)
y2<-rnorm(20)
df2<-data.frame(Class,y2)
df2Output
Class y2 1 Male 0.05278402 2 Female 1.61835971 3 Female 1.17452205 4 Male -0.61445588 5 Female -0.25727985 6 Female 0.75821980 7 Male -1.08398301 8 Male 0.77650504 9 Male 0.54157874 10 Male 0.42124703 11 Male 0.36434790 12 Male -1.03566231 13 Male 0.06208824 14 Male 0.11831360 15 Male 1.22460403 16 Male -2.43157148 17 Male -0.50869299 18 Male -1.14549469 19 Female 1.45219635 20 Male -1.14271790
Finding groupwise number of positive and negative values for Class column in df2 −
Example
df2%>%group_by(Class)%>%mutate(positive=sum(y2>0),negative=sum(y2<0)) # A tibble: 20 x 4 # Groups: Class [2]
Output
Class y2 positive negative <chr> <dbl> <int> <int> 1 Male 0.0528 8 7 2 Female 1.62 4 1 3 Female 1.17 4 1 4 Male -0.614 8 7 5 Female -0.257 4 1 6 Female 0.758 4 1 7 Male -1.08 8 7 8 Male 0.777 8 7 9 Male 0.542 8 7 10 Male 0.421 8 7 11 Male 0.364 8 7 12 Male -1.04 8 7 13 Male 0.0621 8 7 14 Male 0.118 8 7 15 Male 1.22 8 7 16 Male -2.43 8 7 17 Male -0.509 8 7 18 Male -1.15 8 7 19 Female 1.45 4 1 20 Male -1.14 8 7
Updated on: 06-Feb-2021
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