r中的聚合正在删除表中的0计数。如何让它表现出来？

我正在尝试使用

aggregate

中的

FUN

参数生成一个带有

aggregate

的表，以便进一步处理。这是我的密码

var <- c(1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0)

aggregate(var, list(group), FUN = table)

预期结果应如下所示：

  Group.1  x.0  x.1
1       1  61   3
2       2 112   3
3       3  30   2
4       4  21   0

---

我该如何解决这个问题

我们需要将“var”创建为

因子

，其中

级别

指定为0和1。这将确保如果计数为0，则特定列将显示为0

var <- factor(var, levels = 0:1)
out <- aggregate(var, list(group), FUN = table)
out
#   Group.1 x.0 x.1
#1       1  29  21
#2       2  29  21
#3       3  23  27
#4       4   0  50

请注意，这些操作将生成一个带有两列的

矩阵
'x'。以便具有常规的
data.frame
列

do.call(data.frame, out)


或者，如果需要更改，我们也可以得到1s的
和
，然后
重塑

reshape(aggregate(cbind(n = rep(1, length(group))) ~ 
  group+ var, FUN = sum), idvar = 'group', direction = 'wide', timevar = 'var')


如果我们使用的是
tidyverse
，而不是
类中的任何更改，即转换为
因子
，则使用两个变量进行
计数
，然后
将其扩展为“宽”格式

library(tidyverse)
tibble(var, group) %>% 
    count(var, group) %>%
    spread(var, n, fill = 0)
# A tibble: 4 x 3
#  group   `0`   `1`
#  <int> <dbl> <dbl>
#1     1    29    21
#2     2    29    21
#3     3    23    27
#4     4     0    50

库（tidyverse）
TIBLE（变量，组）%>%
计数（变量，组）%>%
排列（变量n，填充=0）
#一个tibble:4x3
#组'0``1`
#    
#1     1    29    21
#2     2    29    21
#3     3    23    27
#4     4     0    50

数据
set.seed（24）
变量
reshape(aggregate(cbind(n = rep(1, length(group))) ~ 
  group+ var, FUN = sum), idvar = 'group', direction = 'wide', timevar = 'var')

library(tidyverse)
tibble(var, group) %>% 
    count(var, group) %>%
    spread(var, n, fill = 0)
# A tibble: 4 x 3
#  group   `0`   `1`
#  <int> <dbl> <dbl>
#1     1    29    21
#2     2    29    21
#3     3    23    27
#4     4     0    50

set.seed(24)
var <- sample(0:1, 200, replace = TRUE)
var[151:200] <- 1
group <- rep(1:4, each = 50)