Aggregate columns for specific groups

[CM1]

Hi,

Using the iris dataset as an example (a small subset below), I need to aggregate (sum) the Petal.Width for each species:

Petal.Width. Species
0.2 setosa
0.2 setosa
0.2 setosa
1.4 versicolor
1.5 versicolor
1.5 versicolor

To result in:
Species Count
setosa 0.6
versicolor 4.4

I've tried various ways of doing this without success. Does anyone have any ideas?

Many thanks for your help

[FJCC]

Here is a solution using the dplyr package.

library(dplyr)

SpeciesSums <- iris %>% group_by(Species) %>% summarize(SUMS = sum(Petal.Width))
SpeciesSums
#> # A tibble: 3 × 2
#>   Species     SUMS
#>   <fct>      <dbl>
#> 1 setosa      12.3
#> 2 versicolor  66.3
#> 3 virginica  101.

^{Created on 2022-04-26 by the reprex package (v0.2.1)}

[CM1]

Brilliant, that's great! I have a wide data frame with many variables, do you know how I can specify a range of variables to sum()?

Many thanks again

[nirgrahamuk]

#by variable property
(SpeciesSums <- iris %>% 
  group_by(Species) %>% 
  summarize(across(where(is.numeric),~sum(.x))))

#by explicit names

vars_to_do <- c("Sepal.Length" ,
                "Sepal.Width" )

(SpeciesSums <- iris %>% 
    group_by(Species) %>% 
    summarize(across(any_of(vars_to_do),~sum(.x))))

[CM1]

@nirgrahamuk

summarize(across(where(is.numeric),~sum(.x)))

That's brilliant, thank you so much! I've been battling with this all day and now its fixed.

Much appreciated