dplyr 用另一列汇总分组数据

Question

我有一个数据框pop.subset <-：

state  location   pop
WA     Seattle    100
WA     Kent       20
OR     foo        30
CA     foo2       80

我需要每个州人口最少的城市存储在data.frame中。我有：

result <- pop.subset %>% 
          group_by(state) %>%
          summarise(min = min(pop))

本returns本data.frame：

state   min
WA      20
...    .... etc

但我也需要这座城市。我试过在 group_by 函数中包含位置，如下所示：group_by(state, location)，但是这给出了每个城市与州配对的最小值，而不是像这样的州与城市配对：

state location pop
WA    Seattle  100
WA    Kent     20
foo   foo      foo

有没有我缺少的简单解决方案？我希望我的结果是这样的：

state location pop
WA    Kent     20
...   ...      ... etc.

Answer 1

你试过这样的事情吗？

result <- pop.subset %>% 
              group_by(state, location) %>%
              summarise(min = min(both_sexes_2012))

Answer 2

我想你想按 state 分组，然后过滤 min(pop):

pop.subset %>% 
  group_by(state) %>% 
  filter(pop == min(pop)) %>%
  ungroup()

# A tibble: 3 x 3
  state location   pop
  <chr>    <chr> <int>
1    WA     Kent    20
2    OR      foo    30
3    CA     foo2    80

Answer 3

我明白了，这样就解决了：

library(tibble)

data<-tribble(~state,  ~location,   ~pop,
       "WA",     "Seattle",    100,
       "WA",    "Kent",       20,
       "OR",     "foo" ,       30,
       "CA",     "foo2" ,      80

)

library(dplyr)

data%>%group_by(state)%>%summarise(location=location[which.min(pop)]
                                   ,min=min(pop))


# A tibble: 3 x 3
  state location   min
  <chr>    <chr> <dbl>
1    CA     foo2    80
2    OR      foo    30
3    WA     Kent    20

dplyr 用另一列汇总分组数据

dplyr summarize grouped data with another column

r

group-by

dplyr

data-manipulation

summarize