根据所有可能的组合将来自不同数据帧的数字相乘

Multiply numbers from different data frames based on all the possible combinations

我有 5 个数据框,如下所示:

df_mon <- data.frame(mon = as.factor(c(6, 7, 8, 9, 10)),
                   number = c(1.11, 1.02, 0.95, 0.92, 0.72))

df_year <- data.frame(year = as.factor(c(1, 2)),
                   number = c(1.61, 0.4))

df_cat <- data.frame(cat = c("A", "B", "C"),
                   number = c(1.11, 1.02, 0.44))

df_bin <- data.frame(bin = as.factor(c(1, 2)),
                      number = c(1.42, 0.56))

df_cat2 <- data.frame(cat2 = c("A", "B", "C", "D", "AA"),
                     number = c(0.11, 1.22, 1.34, 0.88, 0.75))

我需要将每个数据框中 'number' 列中的所有数字相互乘以。因此,查看每个数据集中第一列中所有可能的组合,然后取数并将它们相乘。最终结果数据框应如下所示(前 3 个已完成)

results_df <- data.frame(combi = c("mon6_year1_catA_bin1_cat2A", "mon6_year1_catA_bin1_cat2B",  "mon6_year1_catA_bin1_cat2C"),
                       final_number = c(1.11*1.61*1.11*1.42*0.11, 1.11*1.61*1.11*1.42*1.22, 1.11*1.61*1.11*1.42*1.34))

我们可以看到 results_df 中的第一列显示了用于计算 final_number 的组合。第一个示例显示,mon_df cat 6 (1.11) 中的 'number' 列被提取并乘以以下内容:

这个组合的答案是 1.11 x 1.61 x 1.11 x 1.42 x 0.11 = 0.3098。 第二行显示下一个可能的组合等等。

我不确定如何实现这一点,所以任何帮助将不胜感激!

也许你可以像下面那样尝试expand.grid

lst <- list(df_mon, df_year, df_cat, df_bin, df_cat2)
results_df <- data.frame(
  combi = do.call(
    paste,
    c(do.call(
      expand.grid,
      lapply(lst, function(v) paste0(names(v[1]), v[, 1]))
    ), sep = "_")
  ),
  final_number = Reduce(
    "*",
    do.call(
      expand.grid,
      lapply(lst, `[[`, 2)
    )
  )
)

这给出了

> head(results_df)
                        combi final_number
1  mon6_year1_catA_bin1_cat2A   0.30985097
2  mon7_year1_catA_bin1_cat2A   0.28472792
3  mon8_year1_catA_bin1_cat2A   0.26518777
4  mon9_year1_catA_bin1_cat2A   0.25681342
5 mon10_year1_catA_bin1_cat2A   0.20098441
6  mon6_year2_catA_bin1_cat2A   0.07698161

这是使用 dplyrtidyr 的方法。

df_all <- df_mon %>%
  full_join(df_year, by = character()) %>%  # by = character() ensures cross join
  full_join(df_cat, by = character()) %>%
  full_join(df_bin, by = character()) %>%
  full_join(df_cat2, by = character()) %>%
  pivot_longer(cols = c(-mon, -year, -cat, -bin, -cat2)) %>%
  group_by(mon, year, cat, bin, cat2) %>%
  summarize(final_number = prod(value), .groups = "keep")
# A tibble: 300 x 6
# Groups:   mon, year, cat, bin, cat2 [300]
   mon   year  cat   bin   cat2  final_number
   <fct> <fct> <chr> <fct> <chr>        <dbl>
 1 6     1     A     1     A            0.310
 2 6     1     A     1     AA           2.11 
 3 6     1     A     1     B            3.44 
 4 6     1     A     1     C            3.77 
 5 6     1     A     1     D            2.48 
 6 6     1     A     2     A            0.122
 7 6     1     A     2     AA           0.833
 8 6     1     A     2     B            1.36 
 9 6     1     A     2     C            1.49 
10 6     1     A     2     D            0.978
# ... with 290 more rows

它将来自其他 data.frames 的变量完整地保留为用于进一步分析的列,但是您可以创建 combi 列并添加一些 paste()