R “只保留”;“集群”;元素数最多的

R “只保留”;“集群”;元素数最多的,r,classification,R,Classification,从示例数据开始: > dput(data) structure(list(Country = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("France", "Spain"), class = "factor"), Car = structure(c(6L, 17L,

从示例数据开始:

> dput(data)
structure(list(Country = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L), .Label = c("France", "Spain"), class = "factor"), 
    Car = structure(c(6L, 17L, 7L, 18L, 4L, 13L, 20L, 5L, 14L, 
    21L, 8L, 11L, 15L, 9L, 12L, 16L, 8L, 11L, 15L, 9L, 12L, 19L, 
    3L, 10L, 1L, 2L), .Label = c("Audi_1_EON", "Audi_2_EON", 
    "Ferrari_1_EOD", "Fiat_1_EOD", "Fiat_1_EON", "Mazda_1_EOD", 
    "Mazda_1_EON", "Mercedes_1_EOD", "Mercedes_1_EON", "Mercedes_2_EOD", 
    "Nexia_1_EOD", "Nexia_1_EON", "Opel_1_EOD", "Opel_1_EON", 
    "Peugeot_1_EOD", "Peugeot_1_EON", "Porsche_2_EOD", "Porsche_2_EON", 
    "Tico_1_EON", "VW_1_EOD", "VW_1_EON"), class = "factor"), 
    ValueOfComp = c(13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 
    14L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 
    16L, 12L, 12L, 12L, 12L)), .Names = c("Country", "Car", "ValueOfComp"
), class = "data.frame", row.names = c(NA, -26L))
在提供的
数据中
我们在第一列中有两个不同的国家。在下一列中,我们可以找到分配给每个国家的汽车,在最后一列中是集群的数量

我只想在表中列出每个国家的一个单一类别。它必须是每个国家最大的集群。让我们以法国为例。将两个集群(
13
14
)分配给该国家。很明显,集群14包含更多的元素/汽车。在这种情况下,我希望保留集群14,并从数据中删除集群13


所提供的数据只是一个例子。我的真实数据是一个庞大的表,因此我相信在某些情况下,集群可能包含相同数量的元素,因此,哪一个元素将保留在数据中并不重要。

使用
dplyr
可以:

library(data.table)

data[ValueOfComp %in% setDT(data)[,rle(ValueOfComp), Country][
                                  ,values[which.max(lengths)], Country]$V1,]

    Country            Car ValueOfComp
 1:  France     Fiat_1_EOD          14
 2:  France     Opel_1_EOD          14
 3:  France       VW_1_EOD          14
 4:  France     Fiat_1_EON          14
 5:  France     Opel_1_EON          14
 6:  France       VW_1_EON          14
 7:   Spain Mercedes_1_EOD          15
 8:   Spain    Nexia_1_EOD          15
 9:   Spain  Peugeot_1_EOD          15
10:   Spain Mercedes_1_EON          15
11:   Spain    Nexia_1_EON          15
12:   Spain  Peugeot_1_EON          15
data %>% 
  group_by(Country, ValueOfComp) %>%
  mutate(size = n()) %>%
  group_by(Country) %>%
  filter(size == max(size), ValueOfComp == max(ValueOfComp))

Source: local data frame [12 x 4]
Groups: Country [2]

   Country            Car ValueOfComp  size
    (fctr)         (fctr)       (int) (int)
1   France     Fiat_1_EOD          14     6
2   France     Opel_1_EOD          14     6
3   France       VW_1_EOD          14     6
4   France     Fiat_1_EON          14     6
5   France     Opel_1_EON          14     6
6   France       VW_1_EON          14     6
7    Spain Mercedes_1_EOD          16     6
8    Spain    Nexia_1_EOD          16     6
9    Spain  Peugeot_1_EOD          16     6
10   Spain Mercedes_1_EON          16     6
11   Spain    Nexia_1_EON          16     6
12   Spain     Tico_1_EON          16     6

我们可以使用
plyr
包和
subset
获得

ddply(dat, "Country", subset, ValueOfComp == count(ValueOfComp)$x[which.max(count(ValueOfComp)$freq)])
#   Country            Car ValueOfComp
#1   France     Fiat_1_EOD          14
#2   France     Opel_1_EOD          14
#3   France       VW_1_EOD          14
#4   France     Fiat_1_EON          14
#5   France     Opel_1_EON          14
#6   France       VW_1_EON          14
#7    Spain Mercedes_1_EOD          15
#8    Spain    Nexia_1_EOD          15
#9    Spain  Peugeot_1_EOD          15
#10   Spain Mercedes_1_EON          15
#11   Spain    Nexia_1_EON          15
#12   Spain  Peugeot_1_EON          15

如果有两个大小相同的集群,会发生什么?两个都保留,还是随机选择一个?我在最后一段提到过。随机选择。这对你来说太容易了:)。下面是一种默认选择第一组的方法。