对多列中的每一列使用dplyr和mutate以及单独的条件

2023年6月15日 235次阅读

我试图计算多列(t1,t2,t3)中唯一字符的数量,并将此值放入一个新变量中.是否计算字符取决于与其关联的另一列的值(p1,p2,p3)是否大于或等于0.05.例如.我有以下数据集：

dat <- data.frame(id = c(1,2,3,4,5),t1 = c('a','a','b','b','c'),
            p1 = c(0.98,1,0.5,0.9,1),t2 = c('b',NA,'a','c',NA),
            p2 = c(0.02,NA,0.25,0.10,NA), t3 = c(NA,NA,'c',NA,NA),
            p3 = c(NA,NA,0.25,NA,NA))

我想要计算给定行的列t1,t2,t3中存在的唯一值的数量,并将此数字放入新变量(total)中,该变量应具有如下输出：

output <- data.frame(id = c(1,2,3,4,5),t1 = c('a','a','b','b','c'),
            p1 = c(0.98,1,0.5,0.9,1),t2 = c('b',NA,'a','c',NA),
            p2 = c(0.02,NA,0.25,0.10,NA), t3 = c(NA,NA,'c',NA,NA),
            p3 = c(NA,NA,0.25,NA,NA), total = c(1,1,3,2,1))

使用dplyr我可以使用以下代码计算t1,t2和t3中的唯一字符：

output <- dat %>%
 group_by(id) %>%
 mutate(total = n_distinct(c(t1,t2,t3), na.rm = TRUE))

然而,如果t1,t2或t3将分别计数以实现期望的输出,则我无法设置p1,p2和p3必须> 0.05的条件.有没有办法为每列t1,t2,t3设置这个条件？谢谢您的帮助.

最佳答案 使用tidyverse：

dat %>%
  mutate(t1 = ifelse(p1 >= 0.05, paste(t1), NA), #Applying the condition
         t2 = ifelse(p2 >= 0.05, paste(t2), NA),
         t3 = ifelse(p3 >= 0.05, paste(t3), NA)) %>%
  select(t1, t2, t3, id) %>%
  gather(var, val, -id) %>% #Transforming data from wide to long format
  group_by(id) %>% #Grouping by ID
  mutate(total = n_distinct(val, na.rm = TRUE)) %>% #Calculating the number of unique values
  spread(var, val) %>% #Transforming the data back to wide format
  select(id, total) %>% 
  left_join(dat, by = c("id" = "id"), copy = FALSE) #Joining with the original data 

     id total t1       p1 t2         p2 t3        p3
  <dbl> <int> <fct> <dbl> <fct>   <dbl> <fct>  <dbl>
1    1.     1 a     0.980 b      0.0200 <NA>  NA    
2    2.     1 a     1.00  <NA>  NA      <NA>  NA    
3    3.     3 b     0.500 a      0.250  c      0.250
4    4.     2 b     0.900 c      0.100  <NA>  NA    
5    5.     1 c     1.00  <NA>  NA      <NA>  NA

要么：

dat %>%
  group_by(id) %>%
  mutate(total = paste(t1[p1 >= 0.05], #Applying the condition
                       t2[p2 >= 0.05], 
                       t3[p3 >= 0.05]),
         total = sum(str_count(rawToChar(unique(charToRaw(total))), letters))) #Counting the number of unique characters

     id t1       p1 t2         p2 t3        p3 total
  <dbl> <fct> <dbl> <fct>   <dbl> <fct>  <dbl> <int>
1    1. a     0.980 b      0.0200 <NA>  NA         1
2    2. a     1.00  <NA>  NA      <NA>  NA         1
3    3. b     0.500 a      0.250  c      0.250     3
4    4. b     0.900 c      0.100  <NA>  NA         2
5    5. c     1.00  <NA>  NA      <NA>  NA         1

整体的唯一字符数：

dat %>%
  mutate(t1 = ifelse(p1 >= 0.05, paste(t1), NA), 
         t2 = ifelse(p2 >= 0.05, paste(t2), NA),
         t3 = ifelse(p3 >= 0.05, paste(t3), NA)) %>%
  select(t1, t2, t3, id) %>%
  gather(var, val, -id) %>% 
  mutate(overall = n_distinct(val, na.rm = TRUE)) %>% 
  spread(var, val) %>% 
  select(id, overall) %>% 
  left_join(dat, by = c("id" = "id"), copy = FALSE) 

  id overall t1   p1   t2   p2   t3   p3
1  1       3  a 0.98    b 0.02 <NA>   NA
2  2       3  a 1.00 <NA>   NA <NA>   NA
3  3       3  b 0.50    a 0.25    c 0.25
4  4       3  b 0.90    c 0.10 <NA>   NA
5  5       3  c 1.00 <NA>   NA <NA>   NA
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