r - 用dplyr总结一个因子的计数

Question

我想按列(所有者)对数据框进行分组，并输出一个新的数据框，该数据框在每次观察时都具有每种因子的计数。实际数据帧相当大，并且有10个不同的因素。

这是一些示例输入:

library(dplyr)
df = tbl_df(data.frame(owner=c(0,0,1,1), obs1=c("quiet", "loud", "quiet", "loud"), obs2=c("loud", "loud", "quiet", "quiet")))

  owner  obs1  obs2
1     0 quiet  loud
2     0  loud  loud
3     1 quiet quiet
4     1  loud quiet

我一直在寻找看起来像这样的输出:

out = data.frame(owner=c("0", "0", "1", "1"), observation=c("obs1", "obs2", "obs1", "obs2"), quiet=c(1, 0, 1, 2), loud=c(1, 2, 1, 0))

  owner observation quiet loud
1     0        obs1     1    1
2     0        obs2     0    2
3     1        obs1     1    1
4     1        obs2     2    0

融化使我一路走来:

melted = tbl_df(melt(df, id=c("owner")))

  owner variable value
1     0     obs1 quiet
2     0     obs1  loud
3     1     obs1 quiet
4     1     obs1  loud
5     0     obs2  loud
6     0     obs2  loud
7     1     obs2 quiet
8     1     obs2 quiet

但是最后一步是什么？如果“值”是一个数字，我就去:

melted %>% group_by(owner, variable) %>% summarise(counts=sum(value))

非常感谢!

Answer 1

2017年的答案是

library(dplyr)
library(tidyr)

gather(df, key, value, -owner) %>%
  group_by(owner, key, value) %>%
  tally %>% 
  spread(value, n, fill = 0)

给出输出

Source: local data frame [4 x 4]
Groups: owner, key [4]

  owner   key  loud quiet
* <dbl> <chr> <dbl> <dbl>
1     0  obs1     1     1
2     0  obs2     2     0
3     1  obs1     1     1
4     1  obs2     0     2

在2019年，答案是:

gather(df, key, value, -owner) %>% 
    count(owner, key, value) %>% 
    spread(value, n, fill = 0)