r - 如何总结 R 中的嵌套组

Question

在像 data 这样的数据框中以下:

library(tidyverse)
ID <- c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y","Z", "a","b","c","d")
State <- rep(c("FL", "GA", "SC", "NC", "VA", "GA"), each = 5)
Location <- rep(c("alpha", "beta", "gamma"), each = 10)
Var3 <- rep(c("Bravo", "Charlie", "Delta", "Echo"), times = c(7,8,10,5))
Sex <- rep(c("M","F","M"), times = 10)
data <- data.frame(ID, State, Location, Var3, Sex)

我想返回一个数据框，或者一个包含多个数据框的列表，它总结了数据可以分组的每种方式。我想看看有多少个人 ID s 在每个 State , Location , 和 Var3 ，多少 M和 F在每个 State , Location , 和 Var3 ，多少 Locations在每个 State ，等等......实现这一目标的最佳方法是什么。

Answer 1

我们可以使用 count

library(dplyr)
data %>%
  count(State, Location, Var3, Sex)

另外，获得 rollup/cube分层计数方式，

library(data.table)
rollup(as.data.table(data), j = .N, by = c("State","Location","Var3", "Sex"))
#    State Location    Var3  Sex  N
# 1:    FL    alpha   Bravo    M  3
# 2:    FL    alpha   Bravo    F  2
# 3:    GA    alpha   Bravo    M  2
# 4:    GA    alpha Charlie    F  1
# 5:    GA    alpha Charlie    M  2
# 6:    SC     beta Charlie    F  2
# 7:    SC     beta Charlie    M  3
# 8:    NC     beta   Delta    M  3
# 9:    NC     beta   Delta    F  2
#10:    VA    gamma   Delta    M  4
#11:    VA    gamma   Delta    F  1
#12:    GA    gamma    Echo    F  2
#13:    GA    gamma    Echo    M  3
#14:    FL    alpha   Bravo <NA>  5
#15:    GA    alpha   Bravo <NA>  2
#16:    GA    alpha Charlie <NA>  3
#17:    SC     beta Charlie <NA>  5
#18:    NC     beta   Delta <NA>  5
#19:    VA    gamma   Delta <NA>  5
#20:    GA    gamma    Echo <NA>  5
#21:    FL    alpha    <NA> <NA>  5
#22:    GA    alpha    <NA> <NA>  5
#23:    SC     beta    <NA> <NA>  5
#24:    NC     beta    <NA> <NA>  5
#25:    VA    gamma    <NA> <NA>  5
#26:    GA    gamma    <NA> <NA>  5
#27:    FL     <NA>    <NA> <NA>  5
#28:    GA     <NA>    <NA> <NA> 10
#29:    SC     <NA>    <NA> <NA>  5
#30:    NC     <NA>    <NA> <NA>  5
#31:    VA     <NA>    <NA> <NA>  5
#32:  <NA>     <NA>    <NA> <NA> 30
#    State Location    Var3  Sex  N

或使用 cube

cube(as.data.table(data), j = .N, by = c("State","Location","Var3", "Sex"))
#.   State Location    Var3  Sex  N
#  1:    FL    alpha   Bravo    M  3
#  2:    FL    alpha   Bravo    F  2
#  3:    GA    alpha   Bravo    M  2
#  4:    GA    alpha Charlie    F  1
#  5:    GA    alpha Charlie    M  2
# ---                               
#111:  <NA>     <NA>   Delta <NA> 10
#112:  <NA>     <NA>    Echo <NA>  5
#113:  <NA>     <NA>    <NA>    M 20
#114:  <NA>     <NA>    <NA>    F 10
#115:  <NA>     <NA>    <NA> <NA> 30