dplyr：独特和独特之间的区别

Question

使用 distinct 与 unique 时，结果行数似乎不同。我正在使用的数据集非常庞大。希望代码可以理解。

dt2a <- select(dt, mutation.genome.position, 
  mutation.cds, primary.site, sample.name, mutation.id) %>%
  group_by(mutation.genome.position, mutation.cds, primary.site) %>% 
  mutate(occ = nrow(.)) %>%
  select(-sample.name) %>% distinct()
dim(dt2a)
[1] 2316382       5

## Using unique instead
dt2b <- select(dt, mutation.genome.position, mutation.cds, 
   primary.site, sample.name, mutation.id) %>%
  group_by(mutation.genome.position, mutation.cds, primary.site) %>%
  mutate(occ = nrow(.)) %>%
  select(-sample.name) %>% unique()
dim(dt2b)
[1] 2837982       5

这是我正在使用的文件：

sftp://sftp-cancer.sanger.ac.uk/files/grch38/cosmic/v72/CosmicMutantExport.tsv.gz

     dt = fread(fl)

Answer 1

这似乎是group_by 考虑这种情况的结果

dt<-data.frame(g=rep(c("a","b"), each=3),
    v=c(2,2,5,2,7,7))

dt %>% group_by(g) %>% unique()
# Source: local data frame [4 x 2]
# Groups: g
# 
#   g v
# 1 a 2
# 2 a 5
# 3 b 2
# 4 b 7

dt %>% group_by(g) %>% distinct()
# Source: local data frame [2 x 2]
# Groups: g
# 
#   g v
# 1 a 2
# 2 b 2

dt %>% group_by(g) %>% distinct(v)
# Source: local data frame [4 x 2]
# Groups: g
# 
#   g v
# 1 a 2
# 2 a 5
# 3 b 2
# 4 b 7

当您使用distinct() 而不指明要区分哪些变量时，它似乎使用了分组变量。