Tidyr如何传播到发生的数量

时间:2016-05-21 14:35:58

标签: r count pivot reshape2 tidyr

拥有这样的数据框

other=data.frame(name=c("a","b","a","c","d"),result=c("Y","N","Y","Y","N"))

如何在tidyr或其他函数中使用扩展函数来获取结果Y或N的计数作为列标题,如下所示

name       Y   N
a          2   0
b          0   1

由于

2 个答案:

答案 0 :(得分:13)

这些是许多方面的一些方法:

1)使用库dplyr,您可以简单地对事物进行分组并计入所需的格式:

library(dplyr)
other %>% group_by(name) %>% summarise(N = sum(result == 'N'), Y = sum(result == 'Y'))
Source: local data frame [4 x 3]

    name     N     Y
  <fctr> <int> <int>
1      a     0     2
2      b     1     0
3      c     0     1
4      d     1     0

2)您可以使用tabletidyr点差组合,如下所示:

library(tidyr)
spread(as.data.frame(table(other)), result, Freq)
  name N Y
1    a 0 2
2    b 1 0
3    c 0 1
4    d 1 0

3)您可以使用dplyrtidyr的组合来执行以下操作:

library(dplyr)
library(tidyr)
spread(count(other, name, result), result, n, fill = 0)
Source: local data frame [4 x 3]
Groups: name [4]

    name     N     Y
  <fctr> <dbl> <dbl>
1      a     0     2
2      b     1     0
3      c     0     1
4      d     1     0

答案 1 :(得分:5)

以下是使用dcast

中的data.table的另一个选项
library(data.table)
dcast(setDT(other), name~result, length)
#    name N Y
#1:    a 0 2
#2:    b 1 0
#3:    c 0 1
#4:    d 1 0

虽然table(other)是一个紧凑的选项(来自@ mtoto&#39;评论),但对于大型数据集,使用dcast可能更有效。下面给出了一些基准

set.seed(24)
other1 <- data.frame(name = sample(letters, 1e6, replace=TRUE), 
    result = sample(c("Y", "N"), 1e6, replace=TRUE), stringsAsFactors=FALSE)

other2 <- copy(other1)

gopala1 <- function() other1 %>% 
                          group_by(name) %>%
                          summarise(N = sum(result == 'N'), Y = sum(result == 'Y'))
gopala2 <- function() spread(as.data.frame(table(other1)), result, Freq)
gopala3 <- function() spread(count(other1, name, result), result, n, fill = 0)
akrun <- function() dcast(as.data.table(other2), name~result, length)


library(microbenchmark)
microbenchmark(gopala1(), gopala2(), gopala3(),
                    akrun(), unit='relative', times = 20L)
#      expr      min       lq     mean   median       uq      max neval
# gopala1() 2.710561 2.331915 2.142183 2.325167 2.134399 1.513725    20
# gopala2() 2.859464 2.564126 2.531130 2.683804 2.720833 1.982760    20
# gopala3() 2.345062 2.076400 1.953136 2.027599 1.882079 1.947759    20
#   akrun() 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000    20