How to get a summary table with totals - r

Question

I wonder if there is a more efficient way to get a summary table including totals.
I made a four step procedure here.
data<-iris %>% group_by(Species) %>%
summarise(
Sepal.Len = paste(format(round(median(Sepal.Length),2),nsmall=2) ),
P.len = paste(format(round(median(Petal.Length),2),nsmall=2) ) ,
counts=n() )
datatotal<-iris %>% group_by(.) %>%
summarize(
Sepal.Len = paste(format(round(median(Sepal.Length),2),nsmall=2) ),
P.len = paste(format(round(median(Petal.Length),2),nsmall=2) ) ,
counts=n() )
datatotal<-cbind(Species="Total",datatotal)
final<-rbind(data,datatotal)
final
# A tibble: 4 × 4
Species Sepal.Len P.len counts
* <fctr> <chr> <chr> <int>
1 setosa 5.00 1.50 50
2 versicolor 5.90 4.35 50
3 virginica 6.50 5.55 50
4 Total 5.80 4.35 150

Answer 1

A further improvement on #Richard's answer where everything is in one chain:
iris %>%
group_by(Species) %>%
summarise(
Sepal.Len = median(Sepal.Length),
P.len = median(Petal.Length) ,
counts = n()
) %>%
bind_rows(., iris %>%
summarize(
Sepal.Len = median(Sepal.Length),
P.len = median(Petal.Length) ,
counts = n()
) %>%
mutate(Species = "Total")
) %>%
mutate_each(funs(format(., nsmall = 2, digits = 2)), 2:3)
the result:
# A tibble: 4 × 4
Species Sepal.Len P.len counts
<chr> <chr> <chr> <int>
1 setosa 5.00 1.50 50
2 versicolor 5.90 4.35 50
3 virginica 6.50 5.55 50
4 Total 5.80 4.35 150
Another alternative is using the margins parameter of dcast from the reshape2 package:
dcast(transform(melt(iris, id.vars = 'Species', measure.vars = c('Sepal.Length','Petal.Length')),
counts = ave(value, variable, Species, FUN = length)),
Species + counts ~ variable,
fun.aggregate = median,
margins = 'Species')
the result (unfortunately not exactly as described):
Species counts Sepal.Length Petal.Length
1 setosa 50 5.0 1.50
2 versicolor 50 5.9 4.35
3 virginica 50 6.5 5.55
4 (all) (all) 5.8 4.35

Answer 2

You can simplify the code, by moving the formatting to the final object etc, but it won't make it much faster
data <- iris %>% group_by(Species) %>%
summarise(
Sepal.Len = median(Sepal.Length),
P.len = median(Petal.Length) ,
counts = n()
)
datatotal <- iris %>%
summarize(
Sepal.Len = median(Sepal.Length),
P.len = median(Petal.Length) ,
counts = n()
) %>%
mutate(Species = "Total")
final <- rbind(data, datatotal)
format(final, nsmall = 2, digits = 2)