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r - 通过另一个变量的加权值对一个变量进行排名？

问题描述

超级 R 初学者在这里。我试图通过另一列/变量的加权值来获得某个变量的排名。例如，我有一个如下所示的数据集：

State <- rep(c("MN", "MN", "OR", "OR", "ME", "ME", "CO", "CO", "HI", "HI"), each = 3)
PopA <- c("145", "215", "200", "300", "177", "155", "2013", "89", "102", "3451", 
          "565", "805", "204", "650", "975", "145", "2045", "789", "226", "398", 
          "763","346","987","1236","765","876","95","45","3457","4557")
PopB <- c("190", "7410", "523", "963", "1254", "235", "3140", "4041", "896", "7458",
          "105", "40", "5673", "638", "1444", "673", "257", "4211", "869", "245", 
          "8545","8553","8853","234","635","963","3456","6754","234","2244")
inc1 <- c("55000", "67000", "34000", "17000", "135000", "98000", "54000", "55000", "102000", "170000",
          "75000", "12000", "345000", "23000", "13000", "78000", "112000", "48000", "45000", "89000", 
          "10000", "12000", "16000", "23000", "98000", "96000", "34000", "65000", "59000", "39000" ) 
inc2 <- c("23000", "98000", "45000", "92000", "87000", "55000", "29000", "65000", "59000", "155000", 
          "65000", "23000", "95000", "134000", "76000", "69000", "45000", "95000", "230000", "125000",
          "48000", "97000", "65000", "23000", "16000", "76000", "34500", "76000", "98000", "35000")
data <- data.frame(State, PopA, PopB, inc1, inc2)

我正在尝试获取 4 个名为Overall_rank1_PopA、Overall_rank2_PopB、Rank_by_state1_PopA 和Rank_by_state2_PopB 的新列。在这些列中，我想通过加权总体 A 和加权总体 B 获得整个数据集的 inc1 和 inc2 排名，然后还按状态分组。我想通过popA和popB的加权百分位数（加权分位数？）来做到这一点。

目前，我有：

ranking <- data %>%
  arrange(inc1, inc2) %>%
  mutate(overall_rank1 = rank(inc1, ties.method = "average"), overall_rank2 = rank(inc2, ties.method = "average"))

ranking2 <- ranking %>%
  group_by(State)%>%
  mutate(state_rank1 = rank(inc1, ties.method = "average"), 
         state_rank2 = rank(inc2, ties.method = "average"))

然而，这只给了我有序的、非加权的排名。

有谁知道如何做到这一点？

标签： rrankingrankpercentileranking-functions

解决方案

步骤1：删除原始数据框中整数周围的所有引号（这些使它们充当字符，无法正确排名）

Step2：为加权人口增加创建新列

data %>% mutate(popAGrowth = inc1/PopA) %>% mutate(popBGrowth = inc2/PopB) -> data

Step3：按增长量对每一行进行排名（第一名是最高百分比增长）

data %>% mutate(popAGrowthRank = rank(-popAGrowth)) -> data
data %>% mutate(popBGrowthRank = rank(-popBGrowth)) -> data

Step4：根据“popAGrowth”和“popBGrowth”对每个状态进行排名

data %>% group_by(State) %>% mutate(stateRank1 = rank(-popAGrowth), stateRank2 = rank(-popBGrowth))

我希望这有帮助！（如果您想丢弃我制作的加权列，可以在另一个管道中使用“select()”）

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