获取连续中最频繁出现的值的列名

Question

我有一个如下所示的数据框：

week_0 <- c(5,0,1,0,0,1)
week_1 <- c(5,0,4,0,2,1)
week_2 <- c(5,0,4,0,8,1)
week_3 <- c(5,0,4,0,8,3)
week_4 <- c(1,0,4,0,8,3)
week_5 <- c(1,0,4,0,8,3)
week_6 <- c(1,0,4,0,1,3)
week_7 <- c(1,0,4,0,1,3)
week_8 <- c(1,0,6,0,3,4)
week_9 <- c(2,4,6,7,3,4)
week_10 <- c(2,4,6,7,3,4)
Participant <- c("Lion","Cat","Dog","Snake","Tiger","Mouse")
test_data <- data.frame(Participant,week_0,week_1,week_2,week_3,week_4,week_5,week_6,week_7,week_8,week_9,week_10)

> test_data

    Participant week_0 week_1 week_2 week_3 week_4 week_5 week_6 week_7 week_8 week_9 week_10
1        Lion      5      5      5      5      1      1      1      1      1      2       2
2         Cat      0      0      0      0      0      0      0      0      0      4       4
3         Dog      1      4      4      4      4      4      4      4      6      6       6
4       Snake      0      0      0      0      0      0      0      0      0      7       7
5       Tiger      0      2      8      8      8      8      1      1      3      3       3
6       Mouse      1      1      1      3      3      3      3      3      4      4       4

我想找出一行中比其他值出现更多的值。例如，对于第一行，值为 1。对于第一行，我要返回的输出是

week_4

。对于第二行，出现次数多于其他的值是0。我要返回的输出是

week_0

，等等。所以最终结果应该是：

week_4

，

week_0

，

week_1

，

week_0

，

week_2

，

week_3

。我必须使用：

apply(test_data, 1, function(x) names(which.max(table(x))))

但是我没有得到我正在搜索的结果。关于如何做到这一点有什么建议吗？

Answer 1

您的代码是良好的开端。您可以使用结果

match()

它在行中的第一个位置，然后使用这个位置索引到列名中：

apply(test_data[, -1], 1, function(x) {
  val <- names(which.max(table(x)))
  names(test_data)[-1][[match(val, x)]]
})
# "week_4" "week_0" "week_1" "week_0" "week_2" "week_3"

注意我用

test_data[, -1]

排除

Participant

列；否则，如果没有多次出现的值，代码将返回参与者姓名，这可能不是您想要的。

Answer 2

dplyr

解决方案

add_count

+

slice_max

:

library(dplyr)

test_data %>%
  tidyr::pivot_longer(starts_with('week')) %>%
  add_count(Participant, value) %>%
  slice_max(n, by = Participant, with_ties = FALSE)

# # A tibble: 6 × 4
#   Participant name   value     n
#   <chr>       <chr>  <dbl> <int>
# 1 Lion        week_4     1     5
# 2 Cat         week_0     0     9
# 3 Dog         week_1     4     7
# 4 Snake       week_0     0     9
# 5 Tiger       week_2     8     4
# 6 Mouse       week_3     3     5

---

如果有“领带”并且您想在输出中包含所有领带：

test_data %>%
  tidyr::pivot_longer(starts_with('week')) %>%
  add_count(Participant, value) %>%
  slice_max(n, by = c(Participant, value), with_ties = FALSE) %>%
  slice_max(n, by = Participant)

Answer 3

首先定义一个函数来查找向量的模式：

Mode <- \(x) names(sort(-table(x)))[1]

参考

困难的部分已经完成。现在使用 dplyr 的

rowwise()

和

c_across()

:

library(dplyr)

test_data %>%
  rowwise() %>%
  mutate(
    m = {
      x <- c_across(week_0:week_10) # get row as a vector
      names(x) <- names(test_data)[-1]
      index <- which(x == Mode(x))[1] # first occurence of mode in 'x'
      names(x)[index]
    }
  )

Answer 4

尝试

fmode

来自

collapse

library(collapse)
names(test_data)[-1][max.col(test_data[-1] == dapply(test_data[-1], 
    MARGIN = 1, fmode), "first")]

-输出

[1] "week_4" "week_0" "week_1" "week_0" "week_2" "week_3"