使用数据表按不同顺序对多列进行排名 [英] Ranking multiple columns by different orders using data table

问题描述

在下面的示例中，如何使用不同的顺序对多列进行排名，例如，将y降序排列，将z升序排列?

Using my example below, how can I rank multiple columns using different orders, so for example rank y as descending and z as ascending?

require(data.table)

dt <- data.table(x = c(rep("a", 5), rep("b", 5)),
y = abs(rnorm(10)) * 10, z = abs(rnorm(10)) * 10)

cols <- c("y", "z")

dt[, paste0("rank_", cols) := lapply(.SD, function(x) frankv(x, ties.method = "min")), .SDcols = cols, by = .(x)]

推荐答案

data.table 的 frank()函数具有一些有用的功能，这些功能在基本R的 rank()函数(请参见?frank ).例如，我们可以通过在变量前面加上减号来反转排名顺序:

data.table's frank() function has some useful features which aren't available in base R's rank() function (see ?frank). E.g., we can reverse the order of the ranking by prepending the variable with a minus sign:

library(data.table)
# create reproducible data
set.seed(1L)
dt <- data.table(x = c(rep("a", 5), rep("b", 5)),
                 y = abs(rnorm(10)) * 10, z = abs(rnorm(10)) * 10)
# rank y descending, z ascending
dt[, rank_y := frank(-y), x][, rank_z := frank(z), x][]

    x         y          z rank_y rank_z
 1: a  6.264538 15.1178117      3      4
 2: a  1.836433  3.8984324      5      1
 3: a  8.356286  6.2124058      2      2
 4: a 15.952808 22.1469989      1      5
 5: a  3.295078 11.2493092      4      3
 6: b  8.204684  0.4493361      1      2
 7: b  4.874291  0.1619026      4      1
 8: b  7.383247  9.4383621      2      5
 9: b  5.757814  8.2122120      3      4
10: b  3.053884  5.9390132      5      3

如果有很多列要单独排名，一些列要降序，一些列要升序，我们可以分两步进行

If there are many columns which are to be ranked individually, some descending, some ascending, we can do this in two steps

# first rank all columns in descending order
cols_desc <- c("y")
dt[, paste0("rank_", cols_desc) := lapply(.SD, frankv, ties.method = "min", order = -1L), 
   .SDcols = cols_desc, by = x][]
# then rank all columns in ascending order
cols_asc <- c("z")
dt[, paste0("rank_", cols_asc) := lapply(.SD, frankv, ties.method = "min", order = +1L), 
   .SDcols = cols_asc, by = x][]

    x         y          z rank_y rank_z
 1: a  6.264538 15.1178117      3      4
 2: a  1.836433  3.8984324      5      1
 3: a  8.356286  6.2124058      2      2
 4: a 15.952808 22.1469989      1      5
 5: a  3.295078 11.2493092      4      3
 6: b  8.204684  0.4493361      1      2
 7: b  4.874291  0.1619026      4      1
 8: b  7.383247  9.4383621      2      5
 9: b  5.757814  8.2122120      3      4
10: b  3.053884  5.9390132      5      3

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