我的数据框示例：
df<- structure(list(Var1 = c("A-01", "A-01", "A-02", "A-01", "A-02",
"A-03", "A-01", "A-02", "A-03", "A-04", "A-01", "A-02", "A-03",
"A-04", "A-05", "A-01", "A-02", "A-03", "A-04", "A-05", "A-07",
"A-01", "A-02", "A-03", "A-04", "A-05", "A-07", "A-08", "A-01",
"A-02"), Var2 = c("A-02", "A-03", "A-03", "A-04", "A-04", "A-04",
"A-05", "A-05", "A-05", "A-05", "A-07", "A-07", "A-07", "A-07",
"A-07", "A-08", "A-08", "A-08", "A-08", "A-08", "A-08", "A-09",
"A-09", "A-09", "A-09", "A-09", "A-09", "A-09", "A-11", "A-11"
), value.data = c(1, -1, -1, 1, 1, -1, 1, 1, -1, 1, -1, -1, 1,
-1, -1, 1, NA, -1, 1, 1, -1, -1, -1, 1, -1, 0, 1, -1, 1, 1)), row.names = c(37L,
73L, 74L, 109L, 110L, 111L, 145L, 146L, 147L, 148L, 181L, 182L,
183L, 184L, 185L, 217L, 218L, 219L, 220L, 221L, 222L, 253L, 254L,
255L, 256L, 257L, 258L, 259L, 289L, 290L), class = "data.frame")
因此，每次在“ Var1”或“ Var2”中出现变量时，都会对“ value.data”中不同唯一值的出现次数进行计数。
所以我将有如下摘要表：
df_sum<- data.frame(Var = c(rep("A-01", 4), rep("A-02", 4)), value.data = c(rep(c(1, -1, 0, NA), 2)), sum=c(5,3,0,0,4,3,0,1))
我可以一个子集一个接一个地做。对于数百个变量而言效率不高。
谢谢
如果您将数据转换为长格式，则可以使用 count
library(tidyverse)
df %>%
melt('value.data') %>%
count(value, value.data) %>%
complete(value, value.data, fill = list(n = 0)) %>%
mutate_if(is.numeric, as.integer)
# # A tibble: 36 x 3
# value value.data n
# <chr> <int> <int>
# 1 A-01 - 1 3
# 2 A-01 0 0
# 3 A-01 1 5
# 4 A-01 NA 0
# 5 A-02 - 1 3
# 6 A-02 0 0
# 7 A-02 1 4
# 8 A-02 NA 1
# 9 A-03 - 1 5
# 10 A-03 0 0
# # ... with 26 more rows
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我来说两句