Question

从我的矩阵看起来像：

structure(list(1.5, 1.5, 1.5, 2, 1.5, 1.5, NA, NA, NA, NA, 5, 
15, 15, 1.5, 15, 15, 15, 15, 15, 1.5, 5, 15, 15, 1.5, 15, 
15, 15, 15, 15, 1), .Dim = c(10L, 3L), .Dimnames = list(c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10"), NULL))

我想得到每个级别的计数表。类似的东西：

column level counts
1      1.5    5
1      2      1
2      1.5    2
2      5      1
2      15     7
3      1      1
3      1.5    1
3      5      1
3      15     7

我该怎么做？

我不确定我追求的结构名称，这可能解释了为什么我找不到我想要的东西是不成功的。对不起。

Answer 1

这使用dplyr进行分组，melt从resshape2转换为从宽列格式转换为所有格式。这使用数据框 - 如果您将来使用dput提供数据，则可以使用您拥有的确切结构。

m <- read.table(text="
[,1] [,2] [,3]
1  1.5  5    5   
2  1.5  15   15  
3  1.5  15   15  
4  2    1.5  1.5 
5  1.5  15   15  
6  1.5  15   15  
7  NA   15   15  
8  NA   15   15  
9  NA   15   15  
10 NA   1.5  1 
", header=TRUE) 

library(reshape2)
library(dplyr)

melt(m, na.rm = TRUE) %>%
  group_by(variable, value) %>%
  summarize(n = n())

#   variable value     n
#   <fctr> <dbl> <int>
# 1    X..1.   1.5     5
# 2    X..1.   2.0     1
# 3    X..2.   1.5     2
# 4    X..2.   5.0     1
# 5    X..2.  15.0     7
# 6    X..3.   1.0     1
# 7    X..3.   1.5     1
# 8    X..3.   5.0     1
# 9    X..3.  15.0     7

Answer 2

我冒昧地回答了我自己的问题。它完全基于@ epi99的答案，@ Pradeep的评论让我明白我的数据有些奇怪。它可能远不是最有效的，但我认为像我这样的R新手更容易理解。

它使用reshape2和dplyr个包。如果尚未安装，请安装它们：

install.packages ("reshape2")
install.packages ("dplyr")

然后：

# Import the libraries
library (reshape2) 
library (dplyr) 

# Import the sample data
test_map <- structure(list(1.5, 1.5, 1.5, 2, 1.5, 1.5, NA, NA, NA, NA, 5, 
           15, 15, 1.5, 15, 15, 15, 15, 15, 1.5, 5, 15, 15, 1.5, 15, 
           15, 15, 15, 15, 1), .Dim = c(10L, 3L), .Dimnames = list(c("1", 
           "2", "3", "4", "5", "6", "7", "8", "9", "10"), NULL))

# test_map is a matrix of lists, which does not work well.
# I'm first transforming it into a matrix where each column is numerics. 
# (that's probably not necessary in most cases)
testmap2 <- apply (test_map, 2, as.numeric)

# then melt (reshape2), group_by and count (dplyr)
test_melted <- melt (testmap2, na.rm = TRUE)
test_grouped <- group_by (melted, Var2, value)
test_counted <- count (grouped)

结果：

> test_counted

Source: local data frame [9 x 3]
Groups: Var2 [?]

   Var2 value     n
  <int> <dbl> <int>
1     1   1.5     5
2     1   2.0     1
3     2   1.5     2
4     2   5.0     1
5     2  15.0     7
6     3   1.0     1
7     3   1.5     1
8     3   5.0     1
9     3  15.0     7

Answer 3

您还可以使用data.table：

library(data.table)

编辑：在OP给出结构后，我更改了代码。

mtable <- apply(test_map,2,unlist)
mtable <- data.table(mtable,seq=1:nrow(m)) ##converting to data.table with a dummy key to melt
names(mtable) = c('a','b','c','seq') ##changing names

mfnew <- melt(mtable, id=('seq'))[,2:3,with=T] ##meting the data basis the dummy key so that the data could be gathered in one column
mfnew
setkeyv(mfnew,c("variable","value")) ##optional

final <- mfnew[,list(cnt=.N),by=list(variable,value)][,2:3,with=T]
final
final[!is.na(final$value),]**Output:**

    > final[!is.na(final$value),]
   value cnt
1:   1.5   5
2:   2.0   1
3:   1.5   2
4:   5.0   1
5:  15.0   7
6:   1.0   1
7:   1.5   1
8:   5.0   1
9:  15.0   7

矩阵计数表？

3 个答案: