如何一次组合多个汇总表

Question

请考虑以下数据框：

set.seed(123)
dat <- data.frame(Region = rep(c("a","b"), each=100),
                  State =rep(c("NY","MA","FL","GA"), each = 50),
                  Loc = rep(letters[1:20], each = 5),
                  ID = 1:200,
                  count1 = sample(4, 200, replace=T),
                  count2 = sample(4, 200, replace=T))

Region，State和Loc是用于各个测量的分组变量，每个变量都有唯一的ID编号。对于每个分组变量，我想总结一下count1和count2各个级别的观察次数。通常我将对每对执行以下操作：

#example for count1 and region:
library(tidyverse)
dat%>%
  dplyr::select(Region,count1)%>%
  group_by(count1,Region)%>%
  count()
##or
with(dat, table(Region, count1))

我如何对所有组合执行此操作并将它们包装到一个表（或至少几个按等效长度分组的表，因为它们将根据所使用的分组变量而有所不同）

Answer 1

尝试这样的事情：

Region1 <- dat %>% group_by(Region, count1) %>% 
  summarise(TotalRegion1 = n())

State1 <- dat %>% group_by(State, count1) %>% 
  summarise(TotalState1 = n())

Loc1 <- dat %>% group_by(Loc, count1) %>% 
  summarise(TotalLoc1 = n())

Answer 2

您可以尝试通过[]一次获得“全部”（对于count1）

out <- dat %>%
  select(-ID, -count2) %>%
  pivot_longer(Region:Loc, names_to = "k", values_to = "v") %>%
  group_by(k, v, count1) %>%
  tally() %>%
  ungroup()

out %>%
  filter(k == "Region")
# # A tibble: 8 x 4
#   k      v     count1     n
#   <chr>  <fct>  <int> <int>
# 1 Region a          1    26
# 2 Region a          2    27
# 3 Region a          3    20
# 4 Region a          4    27
# 5 Region b          1    20
# 6 Region b          2    30
# 7 Region b          3    30
# 8 Region b          4    20
out
# # A tibble: 101 x 4
#    k     v     count1     n
#    <chr> <fct>  <int> <int>
#  1 Loc   a          2     5
#  2 Loc   a          3     1
#  3 Loc   a          4     4
#  4 Loc   b          1     2
#  5 Loc   b          2     2
#  6 Loc   b          3     3
#  7 Loc   b          4     3
#  8 Loc   c          1     2
#  9 Loc   c          2     2
# 10 Loc   c          3     3
# # ... with 91 more rows