创建一列，统计变量在R中各列中出现的次数

Question

假设我有这个数据集：

col1 col2 
1   2    1 
2   1    1 
3   1    2 
4   1    2 
5   1    2 
6   1    1 
7   2    1 
8   2    2  

我该如何创建一个统计次数的列；1〃；或"；2〃；显示在各列之间，看起来如下：

col1 col2 count_1 count_2
1   2    1     1      1
2   1    1     2      0
3   1    2     1      1
4   1    2     1      1
5   1    2     1      1
6   1    1     2      0
7   2    1     1      1
8   2    2     0      2

Answer 1

我们可以在创建的逻辑矩阵上使用rowSums，通过循环这些值来比较这些值

df1[paste0("count_", seq_along(df1))] <- lapply(1:2, 
function(x) rowSums(df1 == x))

-输出

> df1
col1 col2 count_1 count_2
1    2    1       1       1
2    1    1       2       0
3    1    2       1       1
4    1    2       1       1
5    1    2       1       1
6    1    1       2       0
7    2    1       1       1
8    2    2       0       2

数据

df1 <- structure(list(col1 = c(2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L), col2 = c(1L, 
1L, 2L, 2L, 2L, 1L, 1L, 2L)), class = "data.frame",
row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8"))

Answer 2

在tidyverse-样式中：

library(dplyr)
library(purrr)
df1 %>% 
mutate(map_dfc(1:2, ~ transmute(df1, "count_{.x}" := rowSums(across(everything()) == .x))))
#   col1 col2 count_1 count_2
# 1    2    1       1       1
# 2    1    1       2       0
# 3    1    2       1       1
# 4    1    2       1       1
# 5    1    2       1       1
# 6    1    1       2       0
# 7    2    1       1       1
# 8    2    2       0       2

Answer 3

如果您正在计算指定列中的数字1到n：

n = 2L
inp_col = sprintf("col%d", 1L:2L)
df[sprintf("count_%d", 1L:n)] = t(apply(df[inp_col], 1L, tabulate, nbins = n))
#   col1 col2 count_1 count_2
# 1    2    1       1       1
# 2    1    1       2       0
# 3    1    2       1       1
# 4    1    2       1       1
# 5    1    2       1       1
# 6    1    1       2       0
# 7    2    1       1       1
# 8    2    2       0       2

数据：

df = data.frame(
col1 = c(2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L),
col2 = c(1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L)
)