rowwise（）do（）與purrr等效，現在該by_row（）已折舊？

Question

現在purrr是by_row（）將是貶值的，什麼是新的首選tidyverse執行情況（是什麼？）：

somedata = expand.grid(a=1:3,b=3,c=runif(3)) 
somedata %>% 
    rowwise() %>% do(binom.test(x=.$a,n=.$b,p=.$c) %>% tidy()) 

看來，如果你還不巢每一行成一列，並然後使用map（），但我不知道如何做嵌套操作...再加上它似乎有點模糊。有沒有更好的辦法？

Answer 1

這裏是map

library(tidyverse) 
library(broom) 
do.call(Map, c(f = binom.test, unname(somedata))) %>% 
     map_df(tidy) 
# estimate statistic p.value parameter conf.low conf.high    method alternative 
#1 0.3333333   1 1.00000000   3 0.008403759 0.9057007 Exact binomial test two.sided 
#2 0.6666667   2 0.25392200   3 0.094299324 0.9915962 Exact binomial test two.sided 
#3 1.0000000   3 0.03571472   3 0.292401774 1.0000000 Exact binomial test two.sided 
#4 0.3333333   1 0.14190440   3 0.008403759 0.9057007 Exact binomial test two.sided 
#5 0.6666667   2 0.55583967   3 0.094299324 0.9915962 Exact binomial test two.sided 
#6 1.0000000   3 1.00000000   3 0.292401774 1.0000000 Exact binomial test two.sided 
#7 0.3333333   1 0.58810045   3 0.008403759 0.9057007 Exact binomial test two.sided 
#8 0.6666667   2 1.00000000   3 0.094299324 0.9915962 Exact binomial test two.sided 
#9 1.0000000   3 0.25948735   3 0.292401774 1.0000000 Exact binomial test two.sided 

---

或只tidyverse功能

somedata %>% 
    unname %>% 
    pmap(binom.test) %>% 
    map_df(tidy) 
#estimate statistic p.value parameter conf.low conf.high    method alternative 
#1 0.3333333   1 1.00000000   3 0.008403759 0.9057007 Exact binomial test two.sided 
#2 0.6666667   2 0.25392200   3 0.094299324 0.9915962 Exact binomial test two.sided 
#3 1.0000000   3 0.03571472   3 0.292401774 1.0000000 Exact binomial test two.sided 
#4 0.3333333   1 0.14190440   3 0.008403759 0.9057007 Exact binomial test two.sided 
#5 0.6666667   2 0.55583967   3 0.094299324 0.9915962 Exact binomial test two.sided 
#6 1.0000000   3 1.00000000   3 0.292401774 1.0000000 Exact binomial test two.sided 
#7 0.3333333   1 0.58810045   3 0.008403759 0.9057007 Exact binomial test two.sided 
#8 0.6666667   2 1.00000000   3 0.094299324 0.9915962 Exact binomial test two.sided 
#9 1.0000000   3 0.25948735   3 0.292401774 1.0000000 Exact binomial test two.sided