How to use the purrr::map() in R

Question

Recently I got to know that the map function from purrr package is really powerful and tried to find out how to use it in the following case:

Using iris dataset and using purrr::map function, calculate max, mean, min for all variables Sepal.Length, Sepal.Width, Petal.Length, Petal.Width, respectively for each Species (setosa, versicolor, virginica). Then put the results into a list having

a character: Species name, and
four vectors: max, mean, min for Sepal.Length, Sepal.Width, Petal.Length, Petal.Width.

Any suggestions? I was using dplyr::mutate, but the result format is not what I want.

iris %>% group_by(Species) %>% summarise(MinSL=min(Sepal.Length), MaxSL=max(Sepal.Length), MeanSL=mean(Sepal.Length), MinPL=min(Petal.Length), MaxPL=max(Petal.Length), MeanPL=mean(Petal.Length))

It will be also nice see if there is a solution using dpylr to do the task. Thank you!

Why not take a look at the purrr tutorial? There are plenty of examples. — Maurits Evers
– Maurits Evers, Commented Apr 20, 2018 at 9:11

Jack Brookes · Accepted Answer · 2018-04-20 09:24:31Z

You don't need purrr. Try:

iris %>% group_by(Species) %>% summarise_at(vars(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width), c("min", "max", "mean"))

Output

# A tibble: 3 x 13 Species Sepal.Length_min Sepal.Width_min Petal.Length_min Petal.Width_min <fct> <dbl> <dbl> <dbl> <dbl> 1 setosa 4.30 2.30 1.00 0.100 2 versicolor 4.90 2.00 3.00 1.00 3 virginica 4.90 2.20 4.50 1.40 # ... with 8 more variables: Sepal.Length_max <dbl>, Sepal.Width_max <dbl>, # Petal.Length_max <dbl>, Petal.Width_max <dbl>, Sepal.Length_mean <dbl>, # Sepal.Width_mean <dbl>, Petal.Length_mean <dbl>, Petal.Width_mean <dbl>

You could even use summarise_allas the summarising function is not applied to the grouping variable.

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