从purrr的pmap（）调用var（）会返回NA

Question

I am trying to use pmap() from the purrr package to simplify my code.

I have a list of vectors x ; all the vectors are the same length. I want to find the mean and variance of all nth elements across all vectors in the list. That is, I want the mean and variance of all the first elements, all the second elements, and so on.

Before the tidyverse , I would convert x to a matrix and use apply() .

x <- list(1:10, 1:10, 1:10)
x_matrix <- do.call(cbind, x)
apply(x_matrix, 1, mean)
##  [1]  1  2  3  4  5  6  7  8  9 10
apply(x_matrix, 1, var)
##  [1] 0 0 0 0 0 0 0 0 0 0

pmap() should allow this without the matrix conversion. pmap_dbl() can replace the apply() and mean() calculation above.

library(purrr)
pmap_dbl(x, mean)
##  [1]  1  2  3  4  5  6  7  8  9 10

However, I cannot get pmap_dbl() and var() and calculation to work. I get NA for every variance.

pmap_dbl(x, var)
##  [1] NA NA NA NA NA NA NA NA NA NA

What am I missing?

Answer 1

We can use ~ and then with ... get the elements, and apply the function

pmap_dbl(x, ~ var(c(...)))

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The reason for different behavior is the difference in the number of parameters in mean and var . In mean , after the object x , other parameters go into ... , while in var , it is not the case, there is x , there is y etc.