如何获取每行中变量的总数

2 回答

• 0

  一个简单的 apply by row就可以了 . 我使用 grep 对data.frame进行子集化，以获取以 "sp" 开头的列 .

  pine <- apply(sp[grep("^sp", names(sp))], 1, function(x) sum(x == "pine"))
  pine
  #[1] 0 1 1
  

  Data.

  sp <- 
  structure(list(Join = 1:3, p1 = 0:2, sp1 = structure(c(1L, 2L, 
  2L), .Label = c("0", "pine"), class = "factor"), p2 = c(0L, 0L, 
  0L), sp2 = c(0L, 0L, 0L), p3 = c(0L, 1L, 0L), sp3 = structure(c(1L, 
  2L, 1L), .Label = c("0", "Aspen"), class = "factor")), class = "data.frame", row.names = c(NA, 
  -3L))
  

  回复于 2024-05-17T00:23:39+08:00
• 0

  您可以长格式转换数据以执行计算 . 一旦数据采用长格式， fuzzyjoin::regex_inner_join 将允许连接配对值的数据（例如 p1 vs sp1 ） .

  使用 tidyverse 的选项可以是：

  library(tidyverse)
  library(fuzzyjoin)         
  
  #To calculate count of Species per row for different type
  
  df %>% gather(Species, value, -Join) %>% 
    mutate(Join = as.character(Join))  %>% {
      regex_inner_join(filter(., grepl("^s",Species)),
                filter(.,grepl("^p",Species)),
                by = c("Join", "Species"))
  } %>%
    filter(value.x != "0") %>%
    group_by(Join.x, value.x) %>%
    summarise(count = sum(as.numeric(value.y))) %>% as.data.frame()
  
  #   Join.x value.x count
  # 1      2   Aspen     1
  # 2      2    pine     1
  # 3      3    pine     2
  
  #To calculate count of Species per row 
  df %>% gather(Species, value, -Join) %>% 
    mutate(Join = as.character(Join))  %>% {
      regex_inner_join(filter(., grepl("^s",Species)),
                filter(.,grepl("^p",Species)),
                by = c("Join", "Species"))
  } %>%
  group_by(Join.x) %>%
  summarise(count = sum(as.numeric(value.y))) %>% as.data.frame()
  
  #   Join.x count
  # 1      1     0
  # 2      2     2
  # 3      3     2
  

  Data:

  df <- read.table(text = 
  "Join      p1     sp1       p2      sp2     p3      sp3
  1          0        0           0         0        0          0
  2          1        pine     0         0       1         Aspen
  3           2        pine     0        0       0          0",
  header = TRUE, stringsAsFactors = FALSE)
  

  回复于 2024-05-17T00:23:39+08:00