将功能应用于一个表的每个条目到另一个表的每个条目 [英] Apply function over every entry one table to every entry of another

问题描述

我想使用bandstib

library(tidyverse)
set.seed(1)
n <- 5
loss <- rbeta(n, 1, 10) * 100

loss.tib <- loss %>% as_tibble %>% mutate(loss = value) %>% mutate(lossid = 
row_number()) %>% select(lossid, loss)
bandstib <- tibble(bandid = seq(4),
                   start = seq(0, 75, by = 25),
                   end = seq(25, 100, by = 25))

bandedlossfn <- function(loss, start, end) {
  pmin(end - start, pmax(0, loss - start))
} 

根据下面的答案，以下代码将产生计算结果:

As per the answer below the following code produces the calculation:

loss.tib %>% 
mutate(
  result = map(
    loss, ~ tibble(result = bandedlossfn(.x, bandstib$start, bandstib$end))
    )
    ) %>% unnest

但是我想将bandid作为索引包含在map函数中，并将filter(!near(result,0))附加于map函数中.

However I'd like to include the bandid as the index within the map function and additionally filter(!near(result,0)) with the map function.

结果应为:

lossid  loss    bandid  result
1   21.6691088  1   21.6691088  
2   6.9390647   1   6.9390647   
3   0.5822383   1   0.5822383   
4   5.5671643   1   5.5671643   
5   27.8237244  1   25.0000000  
5   27.8237244  2   2.8237244   

推荐答案

以下是使用purrr包中的map2的一种可能性:

here is one possibility using map2 from the purrr package:

bandstib %>% 
  mutate(result = map2(start, end, ~bandedlossfn(loss.tib[[1]], .x, .y)))

根据您希望输出的内容，可以从此处继续操作，例如使用unnest.

Depending on how you want your output to be you can continue from there by e.g. using unnest.

编辑

以下是使用map而不是map2的相反方法:

Here is how you can apply it the otherway arround using map instead of map2:

loss.tib %>% 
  mutate(result = map(value, bandedlossfn, start = bandstib$start, end = bandstib$end)) %>%
  unnest() %>% 
  mutate(bandid = rep(seq(4), n))

这篇关于将功能应用于一个表的每个条目到另一个表的每个条目的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！