获取的多个变量/列分类因子数中的R

Question

我在R中的以下小例子：

testing = data.frame(c("Once a week", "Once a week", "Rarely", "Once a month", "Once a month"), c("Once a month", "Once a month", "Once a week", "Rarely", "Rarely")) 
colnames(testing) = c("one", "two") 
testing 

     one   two 
1 Once a week Once a month 
2 Once a week Once a month 
3  Rarely Once a week 
4 Once a month  Rarely 
5 Once a month  Rarely 

我想最终的结果是具有所有可能的绝对因素，一列的数据帧而列的其余部分是这样的每列/变量计数：

categories one two 
Rarely  1  2 
Once a month 2  2 
Once a week 2  1 

我有R上的库没有任何限制所以无论将是最容易在这里（也许plyr/dplyr？）。

谢谢。

Answer 1

表的工作原理，无需外部的包：

sapply(testing, table) 
#    one two 
#Once a month 2 2 
#Once a week 2 1 
#Rarely   1 2 

Answer 2

您可以用tidyr和dplyr包整理好您的桌子和计数与基地table功能

testing = data.frame(c("Once a week", "Once a week", "Rarely", "Once a month", "Once a month"), c("Once a month", "Once a month", "Once a week", "Rarely", "Rarely")) 
colnames(testing) = c("one", "two") 
testing 
#>   one   two 
#> 1 Once a week Once a month 
#> 2 Once a week Once a month 
#> 3  Rarely Once a week 
#> 4 Once a month  Rarely 
#> 5 Once a month  Rarely 

library(tidyr) 
library(dplyr) 

testing %>% 
    gather("type", "categories") %>% 
    table() 
#>  categories 
#> type Once a month Once a week Rarely 
#> one   2   2  1 
#> two   2   1  2 

# or reorder colum before table 
testing %>% 
    gather("type", "categories") %>% 
    select(categories, type) %>% 
    table() 
#>    type 
#> categories  one two 
#> Once a month 2 2 
#> Once a week 2 1 
#> Rarely   1 2 

Answer 3

这里类别真实使用tidyr::gather另一种方式，tidyr::spread和dplyr::count：

library(dplyr) 
library(tidyr) 

testing %>% 
    gather(measure, value) %>% 
    count(measure, value) %>% 
    spread(measure, n) 

# Source: local data frame [3 x 3] 
# 
#   value one two 
#   (chr) (int) (int) 
# 1 Once a month  2  2 
# 2 Once a week  2  1 
# 3  Rarely  1  2 

而且，看到这fantastic gist关于这个话题。