Question

我试图计算多个列（t1，t2，t3）中唯一字符的数量，并将此值放入新变量中。是否计算一个字符取决于与（p1，p2，p3）关联的另一列的值是否大于或等于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))

我希望计算给定行的t1，t2，t3列中存在的唯一值的数量，并将此数量放入新变量（总计）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))

但是，如果要分别计算t1，t2或t3以获得所需的输出，我无法设置p1，p2和p3必须大于等于0.05的条件。有没有办法为每列t1，t2，t3设置此条件？谢谢您的帮助。

Answer 1

您可以添加条件，然后对结果求和。

dat %>% 
  group_by(id) %>% 
  mutate_if(is.factor,as.character) %>%  
  mutate(total = sum(p1>=.05*nchar(t1),p2>=.05*nchar(t2),p3>=.05*nchar(t3),na.rm = T))

# A tibble: 5 x 8
# Groups:   id [5]
#     id t1       p1 t2       p2 t3       p3 total
#  <dbl> <chr> <dbl> <chr> <dbl> <chr> <dbl> <int>
#1     1 a      0.98 b      0.02 NA    NA        1
#2     2 a      1    NA    NA    NA    NA        1
#3     3 b      0.5  a      0.25 c      0.25     3
#4     4 b      0.9  c      0.1  NA    NA        2
#5     5 c      1    NA    NA    NA    NA        1

Answer 2

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

或者：

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

总体上的唯一字符数：

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

对多列中的每列使用dplyr和mutate具有单独的条件

2 个答案: