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如何使用dplyr和tidy评估以编程方式过滤数据帧?

rlang tidyverse dplyr r

tws · 技术社区 · 8 年前

假设我想过滤 starwars

library(tidyverse)

# a function that allows the user to supply filters
filter_starwars <- function(filters) {
  for (filter in filters) {
    starwars = filter_at(starwars, filter$var, all_vars(. %in% filter$values))
  }

  return(starwars)
}

# filter Star Wars characters that are human, and from either Tatooine or Alderaan
filter_starwars(filters = list(
  list(var = "homeworld", values = c("Tatooine", "Alderaan")),
  list(var = "species", values = "Human")
))

但这不允许我指定高度过滤器,因为我已经硬编码了 %in% 中的操作员 .vars_predicate 属于 filter_at() > >= , < , <= == 操作员

filter_starwars() 功能,以便用户可以提供足够通用的过滤器,以沿任何列进行过滤,并使用任何运算符?

filter_()

filter_(starwars, "species == 'Human' & homeworld %in% c('Tatooine', 'Alderaan') & height > 175")

但这一点再次遭到反对。

2 回复 | 直到 8 年前

Weihuang Wong 8 年前

尝试

filter_starwars <- function(...) {
  F <- quos(...)
  filter(starwars, !!!F)
}

filter_starwars(species == 'Human', homeworld %in% c('Tatooine', 'Alderaan'), height > 175)
# # A tibble: 7 Ã 13
#                  name height  mass  hair_color skin_color eye_color birth_year
#                 <chr>  <int> <dbl>       <chr>      <chr>     <chr>      <dbl>
# 1         Darth Vader    202   136        none      white    yellow       41.9
# 2           Owen Lars    178   120 brown, grey      light      blue       52.0
# 3   Biggs Darklighter    183    84       black      light     brown       24.0
# 4    Anakin Skywalker    188    84       blond       fair      blue       41.9
# 5         Cliegg Lars    183    NA       brown       fair      blue       82.0
# 6 Bail Prestor Organa    191    NA       black        tan     brown       67.0
# 7     Raymus Antilles    188    79       brown      light     brown         NA
# # ... with 6 more variables: gender <chr>, homeworld <chr>, species <chr>,
# #   films <list>, vehicles <list>, starships <list>

看见 https://cran.r-project.org/web/packages/dplyr/vignettes/programming.html quos 捕获 ... 作为列表,不评估参数。 !!! filter() .

G. Grothendieck 8 年前

1) 对于这个特殊的问题,我们实际上不需要 filter_ 、rlang或类似产品。这项工作:

filter_starwars <- function(...) {
    filter(starwars, ...)
}

# test
filter_starwars(species == 'Human', 
                homeworld %in% c('Tatooine', 'Alderaan'), 
                height > 175)
)

library(rlang)

filter_starwars <- function(...) {
    filter(starwars, !!!parse_exprs(paste(..., sep = ";")))
}

# test
filter_starwars("species == 'Human'", 
                "homeworld %in% c('Tatooine', 'Alderaan')", 
                "height > 175")

2a)

library(rlang)

filter_starwars <- function(filters) {
    filter(starwars, !!!parse_exprs(paste(filters, collapse = ";")))
}

# test 
filter_starwars(c("species == 'Human'", 
                  "homeworld %in% c('Tatooine', 'Alderaan')", 
                  "height > 175"))