计算 R 中关于列的唯一观察值对之间的关​​系 [英] Calculating a relationship between unique pairs of observations about a colum in R

问题描述

我正在尝试计算两种商品出现在同一组中的概率(按比例计算).

I am trying to calculate the probability, subject to proportion, of two commodities appearing in the same group.

我有以下数据，

data <- data.frame(group = c(1,1,1,1,2,2,2,2,3,3,3,3),
                   commodity = c("Wheat", "Coal", "Steel", "Iron", "Wheat", "Coal", "Steel", "Iron", "Wheat", "Coal", "Steel", "Iron"),
                   quantity = c(5,10,0,5,20,5,10,0,0,10,15,15),
                   proportion = c(0.25,0.5,0,0.25,0.57,0.14,0.29,0,0,0.25,0.375,0.375))

我想计算每种可能的独特商品对的比例(产品总和除以 2).

I would like to do a calculation on the proportion (sum of products divided by 2) for each of the unique possible pairs of commodities.

结果应该是这样的，

result <- data.frame(commodity1 = c("Wheat", "Wheat", "Wheat", "Coal", "Coal", "Steel"),
                     commodity2 = c("Coal", "Steel", "Iron", "Steel", "Iron", "Iron"),
                     result = c(0.103,0.082,0.031,0.067,0.109,0.070))

例如，Wheat - Coal 的结果将计算为 (0.25 * 0.5/2)+(0.57 * 0.14/2)+(0 * 0.25/2)=0.103

Where the result for Wheat - Coal for example, would be calculated (0.25 * 0.5/2)+(0.57 * 0.14/2)+(0 * 0.25/2)=0.103

我已将商品对隔离到单独的 data.frame 中以将结果变异为并尝试 rowwise() 操作.

I have isolated the commodity pairs into a separate data.frame to mutate the result into and attempted a rowwise() operation.

任何建议将不胜感激.

推荐答案

虽然不是很干净，但似乎有效

Though not much of clean, it seems working

library(tidyverse)

#make an intermediate data.frame say `dd`
data %>% select(-quantity) %>%
  pivot_longer(proportion) %>%
  select(-name, -group) %>%
  group_by(commodity) %>%
  nest(data = c(value)) -> dd


t(combn(unique(data$commodity), 2)) %>% as.data.frame() %>%
  mutate(result = map2_dbl(V1, V2, 
                        ~ sum(unlist(dd$data[match(.x, dd$commodity)]) * unlist(dd$data[match(.y, dd$commodity)]))/2
                      )
         )

     V1    V2    result
1 Wheat  Coal 0.1024000
2 Wheat Steel 0.0826500
3 Wheat  Iron 0.0312500
4  Coal Steel 0.0671750
5  Coal  Iron 0.1093750
6 Steel  Iron 0.0703125

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