Question

对于以下数据框，我想使用“ mutate”基于“ Type”列值创建新列，并计算出现的实例数。数据应按“组”和“选择”进行分组。

随着时间的流逝，“类型”列将添加尚未列出的新值，因此代码在这方面应具有灵活性。

使用dplyr库是否有可能？

library(dplyr)

df <- data.frame(Group = c("A","A","A","B","B","C","C","D","D","D","D","D"),
             Choice = c("Yes","Yes","No","No","Yes","Yes","Yes","Yes","No","No","No","No"),
             Type = c("Fruit","Construction","Fruit","Planes","Fruit","Trips","Construction","Cars","Trips","Fruit","Planes","Trips"))

所需的结果应为以下内容：

result <- data.frame(Group = c("A","A","B","B","C","D","D"),
                 Choice = c("Yes","No","Yes","No","Yes","Yes","No"),
                 Fruit = c(1,1,0,1,0,0,1),
                 Construction = c(0,1,0,0,1,0,0),
                 Planes = c(0,0,1,0,0,0,1),
                 Trips = c(0,0,0,0,1,0,2),
                 Cars = c(0,0,0,0,0,1,0))

Answer 1

我们可以先计数，然后spread

library(tidyverse)
df %>% 
   count(Group, Choice, Type) %>%
   spread(Type, n, fill = 0)
# A tibble: 7 x 7
#  Group Choice  Cars Construction Fruit Planes Trips
#  <fct> <fct>  <dbl>        <dbl> <dbl>  <dbl> <dbl>
#1 A     No         0            0     1      0     0
#2 A     Yes        0            1     1      0     0
#3 B     No         0            0     0      1     0
#4 B     Yes        0            0     1      0     0
#5 C     Yes        0            1     0      0     1
#6 D     No         0            0     1      1     2
#7 D     Yes        1            0     0      0     0

使用mutate从列值创建列

1 个答案: