列值排名 [英] Rank values column-wise

问题描述

我想按列对值进行排名。

I want to rank values column-wise.

我有以下数据框：

dput(test)
structure(list(Name = c("A", "B", "C", "D"), Margin = c(744, 
3196.4722, 0, 394), T1 = c(420, 200, 2150, 70), T2 = c(630, 285, 
2365, 84), T3 = c(630, 335, 2580, 105), T4 = c(666, 410, 2795, 
128), T5 = c(2244, 2961.7931, 3010, 142), T6 = c(2244, 3652.472, 
3440, 151), T7 = c(2244, 3722.472, 3870, 168), T8 = c(2244, 3887.472, 
5160, 187), T9 = c(2244, 4112.472, 6450, 225), T10 = c(2244, 
4337.472, 6450, 225), T11 = c(798, 3567.472, 4300, 112), T12 = c(630, 
3582.472, 4300, 111), T13 = c(702, 3582.472, 4300, 112), T14 = c(3600, 
4637.472, 3440, 78), T15 = c(744, 3067.306, 2580, 274), T16 = c(744, 
2770.5666, 2580, 197), T17 = c(744, 3138.806, 2580, 80), T18 = c(2244, 
3920.0836, 3870, 401), T19 = c(2244, 2789.1117, 1290, 127)), .Names = c("Name", 
"Margin", "T1", "T2", "T3", "T4", "T5", "T6", "T7", "T8", "T9", 
"T10", "T11", "T12", "T13", "T14", "T15", "T16", "T17", "T18", 
"T19"), row.names = c(NA, -4L), class = c("tbl_df", "tbl", "data.frame"
))

每行都有唯一的名称中的ID，我想对列进行排名，以确定哪一列等于或小于margin列中的值。

Each row has unique ID in name, and I want to rank the columns to determine which column is equal or least small to the value in the margin column.

理想的输出为：

Name    Margin    Closest_Column
 A      744.000        T15

断裂带可能是随机的。

Break ties could be random.

我的尝试：

nm1 <- paste("rank", names(test)[3:21], sep="_")
test[nm1] <-  mutate_all(test[3:21],funs(rank(., ties.method="first")))

推荐答案

如果需要使用 tidyverse ，一种方法是 rowwise ，然后找到保证金与其他列之间的最小差值的索引以获取列名

If we need to use tidyverse, one approach is rowwise and then find the index of the minimum difference between the 'Margin' and other columns to get the column names

test %>% 
      rowwise() %>% 
      do(data.frame(.[1:2], Closest_column = names(.)[3:21][which.min(abs(.[[2]]-
                        unlist(.[3:21])))]))
# A tibble: 4 x 3
#    Name   Margin Closest_column
#* <chr>    <dbl>          <chr>
#1     A  744.000            T15
#2     B 3196.472            T17
#3     C    0.000            T19
#4     D  394.000            T18

---

或者另一个选择是

---

Or another option is

library(tidyverse)
gather(test, Closest_column, val, T1:T19) %>%
        group_by(Name) %>% 
        slice(which.min(abs(Margin - val))) %>%
        select(-val)
# A tibble: 4 x 3
# Groups:   Name [4]
#    Name   Margin Closest_column
#  <chr>    <dbl>          <chr>
#1     A  744.000            T15
#2     B 3196.472            T17
#3     C    0.000            T19
#4     D  394.000            T18

---

使用 base R ，有效的选择是 max.col

cbind(test[1:2], 
    Closest_column = names(test)[3:21][max.col(-abs(test[3:21]-test[[2]]), 'first')])
#    Name   Margin Closest_column
#1    A  744.000            T15
#2    B 3196.472            T17
#3    C    0.000            T19
#4    D  394.000            T18

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