如何在不丢失行的情况下在R中子集一个平面列联表&；列名？

我正在使用ftable创建一个平面列联表。但是，当我对列联表进行子集设置时，R会删除行和列名。是否有办法将表子集化，使行和列名保留在子集表中？下面是一个例子：

# Create fake data
Group1 = sample(LETTERS[1:3], 20, replace=TRUE)
Group2 = sample(letters[1:3], 20, replace=TRUE)
Year = sample(c("2010","2011","2012"), 20, replace=TRUE)
df1 = data.frame(Group1, Group2, Year)

# Create flat contingency table with column margin
table1 = ftable(addmargins(table(df1$Group1, df1$Group2, df1$Year), margin=3))

# Select rows with sum greater than 2
table2 = table1[table1[ ,4] > 2, ]

> table1
     2010 2011 2012 Sum

A a     0    1    2   3
  b     2    1    0   3
  c     0    0    0   0
B a     0    1    1   2
  b     2    0    0   2
  c     1    0    1   2
C a     0    1    0   1
  b     1    0    2   3
  c     3    0    1   4

> table2
     [,1] [,2] [,3] [,4]
[1,]    0    1    2    3
[2,]    2    1    0    3
[3,]    1    0    2    3
[4,]    3    0    1    4

---

注意R是如何将子集表转换为矩阵的，去掉了列名和两个级别的行名。如何将ftable结构保留在子列表中

结果将不再是

ftable

对象， 因为有些组合丢失了

但是您可以使用一个矩阵，其中包含行和列名

ftable_names <- function(x, which="row.vars") {
  # Only tested in dimensions 1 and 2
  rows <- as.vector(Reduce( 
    function(u,v) t(outer(as.vector(u),as.vector(v),paste)), 
    attr(x, which), 
    "" 
  ))
}
i <- table1[ ,4] > 2
table2 <- table1[i,]
rownames(table2) <- ftable_names(table1, "row.vars")[i]
colnames(table2) <- ftable_names(table1, "col.vars")
table2

#      2010  2011  2012  Sum
# A a     1     2     0    3
# A c     0     0     3    3
# B c     0     3     0    3
# C a     3     1     1    5

---

ftable_name考虑使用频率数据帧。它是一个更好的数据结构，尤其是当您要对其进行过滤时。下面是一种使用重塑包构建一个的方法

# cast the data into a data.frame
library(reshape)
df1$Freq <- 1
df2 <- cast(df1, Group1 + Group2 ~ Year, fun = sum, value = "Freq")
df2
#   Group1 Group2 2010 2011 2012
# 1      A      a    0    0    1
# 2      A      b    1    1    3
# 3      A      c    0    0    1
# 4      B      a    1    2    0
# 5      B      b    1    1    0
# 6      B      c    0    0    1
# 7      C      a    2    0    1
# 8      C      b    2    0    0
# 9      C      c    0    0    2

# add a column for the `Sum` of frequencies over the years
df2 <- within(df2, Sum <- `2010` + `2011` + `2012`)
df2
#   Group1 Group2 2010 2011 2012 Sum
# 1      A      a    0    0    1   1
# 2      A      b    1    1    3   5
# 3      A      c    0    0    1   1
# 4      B      a    1    2    0   3
# 5      B      b    1    1    0   2
# 6      B      c    0    0    1   1
# 7      C      a    2    0    1   3
# 8      C      b    2    0    0   2
# 9      C      c    0    0    2   2

df2[df2$Sum > 2, ]
#   Group1 Group2 2010 2011 2012 Sum
# 2      A      b    1    1    3   5
# 4      B      a    1    2    0   3
# 7      C      a    2    0    1   3

#将数据强制转换为data.frame
图书馆（重塑）
df1$Freq
ftable
创建“扁平”列联表[by]。。。将数据重新排列为[2D]矩阵。因此，只需使用
as.matrix
在子集之前将数据转换为矩阵（如果直接使用
as.table
，数据将返回到它的高维结构）

编辑
或者使用
dplyr
和
tidyr
软件包，以提高代码的灵活性和可读性：

library(dplyr)
library(tidyr)

df1 %>% 
  group_by(Group1, Group2, Year) %>%
  tally() %>%
  spread(Year, n, fill = 0) %>%
  ungroup() %>% 
  mutate(Sum = rowSums(.[-(1:2)])) %>%
  filter(Sum > 2) %>%
  unite(Name, c(Group1, Group2), sep = " ")

Source: local data frame [5 x 5]

   Name  2010  2011  2012   Sum
  (chr) (dbl) (dbl) (dbl) (dbl)
1   A a     2     1     0     3
2   A b     1     1     1     3
3   B b     2     0     2     4
4   B c     1     2     0     3
5   C a     1     2     0     3

dimnames(mat2) <- rapply(dimnames(mat2), gsub, pattern = "_", replacement = " ", how = "replace")

library(dplyr)
library(tidyr)

df1 %>% 
  group_by(Group1, Group2, Year) %>%
  tally() %>%
  spread(Year, n, fill = 0) %>%
  ungroup() %>% 
  mutate(Sum = rowSums(.[-(1:2)])) %>%
  filter(Sum > 2) %>%
  unite(Name, c(Group1, Group2), sep = " ")

Source: local data frame [5 x 5]

   Name  2010  2011  2012   Sum
  (chr) (dbl) (dbl) (dbl) (dbl)
1   A a     2     1     0     3
2   A b     1     1     1     3
3   B b     2     0     2     4
4   B c     1     2     0     3
5   C a     1     2     0     3