如何将变量引用和取消引用到函数中以及如何遍历数据框

Question

我正在尝试使用一个函数并遍历值的数据框架。这里的目标是按10个一组总结机场延误。

如何将传递给函数的值作为名称？列原点（EWR，LGA，JFK）应另存为列，并且仍需要按功能传递给组。

library(tidyverse)
library(nycflights13)

head(flights)
#> # A tibble: 6 x 19
#>    year month   day dep_time sched_dep_time dep_delay arr_time sched_arr_time
#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>          <int>
#> 1  2013     1     1      517            515         2      830            819
#> 2  2013     1     1      533            529         4      850            830
#> 3  2013     1     1      542            540         2      923            850
#> 4  2013     1     1      544            545        -1     1004           1022
#> 5  2013     1     1      554            600        -6      812            837
#> 6  2013     1     1      554            558        -4      740            728
#> # ... with 11 more variables: arr_delay <dbl>, carrier <chr>, flight <int>,
#> #   tailnum <chr>, origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>,
#> #   hour <dbl>, minute <dbl>, time_hour <dttm>

ntile_summary <- function(data, by, var) {
  by <- enquo(by)
  var <- enquo(var)
  data %>%
    mutate(pcts = ntile(!!by, n = 10),
           col_nm = !!by)
    group_by(pcts, col_nm) %>% 
      summarize(avg = mean(!!var, na.ram  = TRUE))
}

params <- expand_grid(
  flights %>% count(origin) %>%  select(origin), 
  flights %>%  count(day) %>% head(2) %>% select(day)
)

ntile_summary(flights, day, arr_delay)
#> Error in group_by(pcts, col_nm): object 'pcts' not found

purrr::walk(params, ~ntile_summary(flights, !origin, arr_delay))
#> Error in !origin: invalid argument type

^{由reprex package（v0.3.0）在2020-03-15创建}

Answer 1

mutate之后，就是连接。不在%>%

ntile_summary <- function(data, by, var) {
 by <- enquo(by)
 var <- enquo(var)
 data %>%
    mutate(pcts = ntile(!!by, n = 10),
       col_nm = !!by) %>%
    group_by(pcts, col_nm) %>% 
    summarize(avg = mean(!!var, na.ram  = TRUE))
}
ntile_summary(flights, day, arr_delay)
# A tibble: 40 x 3
# Groups:   pcts [10]
#    pcts col_nm   avg
#   <int>  <int> <dbl>
# 1     1      1 NA   
# 2     1      2 NA   
# 3     1      3 NA   
# 4     1      4 -4.44
# 5     2      4 NA   
# 6     2      5 NA   
# 7     2      6 NA   
# 8     2      7 NA   
# 9     3      7 NA   
#10     3      8 NA   
# … with 30 more rows

---

我们也可以使用卷曲卷曲运算符（{{}}）代替enquo +`!!〜

ntile_summary <- function(data, by, var) {

     data %>%          
        mutate(col_nm = {{by}}, pcts = ntile({{by}}, n = 10)) %>% 
        group_by(pcts, col_nm) %>%
        summarize(avg = mean({{var}}, na.ram  = TRUE))
    }

ntile_summary(flights, day, arr_delay)
# A tibble: 40 x 3
# Groups:   pcts [10]
#    pcts col_nm   avg
#   <int>  <int> <dbl>
# 1     1      1 NA   
# 2     1      2 NA   
# 3     1      3 NA   
# 4     1      4 -4.44
# 5     2      4 NA   
# 6     2      5 NA   
# 7     2      6 NA   
# 8     2      7 NA   
# 9     3      7 NA   
#10     3      8 NA   
# … with 30 more rows