R - 按中断进行切割并按组计算出现次数

Question

我有一个如下所示的数据框：

dat <- structure(list(Geocode = c("1100015", "1100023", "1100031", "1100049", 
"1100056", "1100064", "1100072", "1100080", "1100098", "1100106", 
"1100114", "1100122", "1100130", "1100148", "1100155", "1100189", 
"1100205", "1100254", "1100262", "1100288", "1100296", "1100304", 
"1100320", "1100338", "1100346", "1100379", "1100403", "1100452", 
"1100502", "1100601"), Location = c("Alta Floresta D'oeste, RO", 
"Ariquemes, RO", "Cabixi, RO", "Cacoal, RO", "Cerejeiras, RO", 
"Colorado Do Oeste, RO", "Corumbiara, RO", "Costa Marques, RO", 
"Espigo D'oeste, RO", "Guajar-Mirim, RO", "Jaru, RO", "Ji-Paran, RO", 
"Machadinho D'oeste, RO", "Nova Brasilndia D'oeste, RO", "Ouro Preto Do Oeste, RO", 
"Pimenta Bueno, RO", "Porto Velho, RO", "Presidente Mdici, RO", 
"Rio Crespo, RO", "Rolim De Moura, RO", "Santa Luzia D'oeste, RO", 
"Vilhena, RO", "So Miguel Do Guapor, RO", "Nova Mamor, RO", "Alvorada D'oeste, RO", 
"Alto Alegre Dos Parecis, RO", "Alto Paraso, RO", "Buritis, RO", 
"Novo Horizonte Do Oeste, RO", "Cacaulandia, RO"), Region = c("Norte", 
"Norte", "Norte", "Norte", "Norte", "Norte", "Norte", "Norte", 
"Norte", "Norte", "Sul", "Sul", "Sul", "Sul", "Sul", 
"Sul", "Sul", "Sul", "Sul", "Sul", "Nordeste", "Nordeste", 
"Nordeste", "Nordeste", "Nordeste", "Nordeste", "Nordeste", "Nordeste", "Nordeste", 
"Nordeste"), Population = c(25578L, 104401L, 6355L, 87226L, 17986L, 
18817L, 8842L, 16651L, 32385L, 46632L, 55738L, 130419L, 37167L, 
21592L, 39924L, 37512L, 502748L, 22557L, 3750L, 56242L, 8532L, 
91801L, 23933L, 27600L, 17063L, 13940L, 20210L, 37838L, 10276L, 
6367L)), .Names = c("Geocode", "Location", "Region", "Population"
), row.names = c(NA, 30L), class = "data.frame")

它显示了一些城市的人口以及这些城市所属的区域。

我需要将人口划分为间隔 ( breaks=c(0,50000,100000))，然后根据间隔查找城市的数量，包括整体（所有区域）和按区域划分的数量。

生成的数据框应如下所示（随机、假设值）：

Class                  Region       Count
[0-50000]               Norte        7
[50000-100000]          Norte        3
[>100000]               Norte        0
[0-50000]               Sul          5
[50000-100000]          Sul          4
[>100000]               Sul          1
[0-50000]               Nordeste     4
[50000-100000]          Nordeste     5
[>100000]               Nordeste     1
[0-50000]               All          16
[50000-100000]          All          12
[>100000]               All          2

任何帮助表示赞赏。

Answer 1

通过使用cut和dplyr

dat$Class=cut(dat$Population,c(0,50000,100000,Inf),labels=c('0-50000','50000-100000','>100000'))
library(dplyr)
d1=dat%>%group_by(Class,Region)%>%summarise(count=n())
d2=dat%>%group_by(Class)%>%summarise(count=n(),Region='All')
bind_rows(d1,d2)

          Class   Region count
         <fctr>    <chr> <int>
 1      0-50000 Nordeste     9
 2      0-50000    Norte     8
 3      0-50000      Sul     6
 4 50000-100000 Nordeste     1
 5 50000-100000    Norte     1
 6 50000-100000      Sul     2
 7      >100000    Norte     1
 8      >100000      Sul     2
 9      0-50000      All    23
10 50000-100000      All     4
11      >100000      All     3