R sf::st_convex_hull()丢失具有多个组的数据的sf类

Question

我正在尝试使用R中的sf创建一个95%的最小凸多边形。只要我只对一个变量进行分组，我的代码就可以正常工作，但是当我对两个变量进行分组时，输出就会失去sf类，而变成一个grouped_df。

以下是一个玩具数据集作为示例

library(dplyr) 
set.seed(12)
toy <- tibble::tibble(
    ID = rep(c(1,2), each = 10),
    year = rep(c(1,2), 10),
    lat = runif(20, 1, 10),
    long = runif(20, 1, 10)
  ) %>%
    sf::st_as_sf(., coords = c("long", "lat")) 
toy %>%
  group_by(ID) %>% 
  summarize(.groups = "keep") %>% 
  mutate(cent = sf::st_centroid(geometry)) %>%
  sf::st_cast(to = "POINT") %>%  
  mutate(dist = sf::st_distance(geometry, cent, by_element = TRUE)) %>% 
  filter(dist <= quantile(dist, .95)) %>% 
  summarize()  %>%
  sf::st_convex_hull() %>%
  class()

这给出了我想要的输出。但是当我尝试按两个变量进行分组时，结果丢失了sf类。

toy %>%
  group_by(ID, year) %>% 
  summarize(.groups = "keep") %>% 
  mutate(cent = sf::st_centroid(geometry)) %>%
  sf::st_cast(to = "POINT") %>%  
  mutate(dist = sf::st_distance(geometry, cent, by_element = TRUE)) %>% 
  filter(dist <= quantile(dist, .95)) %>% 
  summarize()  %>%
  sf::st_convex_hull() %>%
  class

是不是我的代码中有什么东西让我无法对两个变量进行分组？

Answer 1

这是因为第二个汇总是对ID进行重新分组，您需要一个.groups = "keeps"来传递相同的分组，然后将其转换回sf对象。或者，您可以创建一个分组变量mutate(grp = paste0(ID, year))并执行group_by(grp)。

toy %>%
  group_by(ID, year) %>% 
  summarize(.groups = "keep") %>% 
  mutate(cent = sf::st_centroid(geometry)) %>%
  sf::st_cast(to = "POINT") %>%  
  mutate(dist = sf::st_distance(geometry, cent, by_element = TRUE)) %>% 
  filter(dist <= quantile(dist, .95)) %>% 
  summarize(.groups = "keep")  %>%
  sf::st_convex_hull() %>%
  st_sf()

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