按两列对数据进行分组和过滤分组(dplyr) [英] group data and filter groups by two columns (dplyr)

问题描述

我对使用 dplyr 过滤数据集有疑问.

I have a question regarding using dplyr to filter a dataset.

我想按其 RestaurantID 对数据进行分组，然后对 wage> = 5 中中的 wage&== 5 的所有组进行分组Year == 1992 .

I want to group data by its RestaurantID and then filter() all groups where the wage >= 5 in Year==1992.

例如:

我有:

 RestaurantID     Year        Wage
     1             92          6
     1             93          4
     2             92          3
     2             93          4
     3             92          5
     3             93          5

我想要的数据集(该数据集将所有在1992年的工资值等于> = 5的组保留下来)

Dataset I want (where it keeps all groups that had a wage value in 1992 that was >= 5)

 RestaurantID     Year        Wage
     1             92          6
     1             93          4
     3             92          5
     3             93          5

我尝试过:

data %>% group_by("RestaurantID") %>% filter(any(Wage>= '5', Year =='92')) 

但这给了我工资为> = 5 的所有行.

But this gives me all rows where wage is >=5.

推荐答案

我们可以在不使用 filter

library(dplyr)
df1 %>% 
    filter(RestaurantID %in% RestaurantID[Year==92 & Wage>= 5])
#   RestaurantID Year Wage
#1            1   92    6
#2            1   93    4
#3            3   92    5
#4            3   93    5

---

或与 base R

subset(df1, RestaurantID %in% RestaurantID[Year==92 & Wage>= 5])
#   RestaurantID Year Wage
#1            1   92    6
#2            1   93    4
#5            3   92    5
#6            3   93    5

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