有条件和分组的mutate dplyr [英] Conditional and grouped mutate dplyr

问题描述

让我们说一下每个抽屉的袜子增加量的以下数据

Lets say I have the following data of sock increase per drawer

>socks
year  drawer_nbr  sock_total
1990    1           2
1991    1           2
1990    2           3
1991    2           4
1990    3           2
1991    3           1

我想有一个二进制变量，该变量标识袜子在每个抽屉中是否增加了.如果增加，则为1；否则，则为0.结果将是

I would like to have a binary variable that identifies if the socks have increased in each drawer. 1 if they increased and 0 if not. The result would be

>socks
drawer_nbr  growth
  <dbl>     <factor>
    1          0  
    2          1
    3          0

在比较一年的 sock_total 与另一年的 sock_total 时，我陷入了困境.我知道我需要使用 dplyr :: summaries()，但是我对该函数内部的内容有困难.

I am getting stuck on comparing sock_total of one year vs sock_total of another year. I know that I need to use dplyr::summaries(), but I am having difficulty with what goes inside that function.

推荐答案

如果将1991年与1990年进行比较，则可以执行以下操作:

If you are comparing year 1991 with 1990, you can do:

socks %>% 
    group_by(drawer_nbr) %>% 
    summarise(growth = +(sock_total[year == 1991] - sock_total[year == 1990] > 0))
# A tibble: 3 x 2
#  drawer_nbr growth
#       <int>  <int>
#1          1      0
#2          2      1
#3          3      0

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