在带有tidyeval(quo_name)的自制函数中使用管道 [英] Using the pipe in selfmade function with tidyeval (quo_name)

问题描述

我有两个功能:date_diff和group_stat.因此，我已阅读 tidyverse 的文章，并尝试创建简单的函数并使用管道.

I have two functions: date_diff and group_stat. So I have read this article tidyverse and I try so create simple functions and use the pipe.

第一个函数创建一个difftime并将其命名为timex_minus_timey，但是当我将此结果通过管道传递到下一个函数时，我必须查看名称，以便我可以填写summary_var.有一个更好的方法吗?

The first function creates a difftime and names them timex_minus_timey but when I pipe this result into the next function I have to look at the name so I can fill in summary_var. Is there a better way to do this?

library(tidyverse)
# 
set.seed(42)
data <- dplyr::bind_rows(
  tibble::tibble(Hosp = rep("A", 1000),
                 drg = sample(letters[1:5], 1000, replace = TRUE),
                 time1 = as.POSIXlt("2018-02-03 08:00:00", tz = "UTC") + rnorm(1000, 0, 60*60*60),
                 time2 = time1 + runif(1000, min = 10*60, max = 20*60)),

  tibble::tibble(Hosp = rep("B", 1000),
                 drg = sample(letters[1:5], 1000, replace = TRUE),
                 time1 = as.POSIXlt("2018-02-03 08:00:00", tz = "UTC") + rnorm(1000, 0, 60*60*60),
                 time2 = time1 + runif(1000, min = 10*60, max = 20*60))
)



date_diff <- function(df, stamp1, stamp2, units = "mins"){

  stamp1 <- rlang::enquo(stamp1)
  stamp2 <- rlang::enquo(stamp2)

  name <- paste0(rlang::quo_name(stamp1), "_minus_", rlang::quo_name(stamp2))

  out <- df %>%
    dplyr::mutate(!!name := as.numeric(difftime(!!stamp1, !!stamp2, units=units)))

  out
}


group_stat <- function(df, group_var, summary_var, .f) {

  func <- rlang::as_function(.f)

  group_var <-  rlang::enquo(group_var)
  summary_var <-rlang::enquo(summary_var)

  name <- paste0(rlang::quo_name(summary_var), "_", deparse(substitute(.f)))

  df %>%
    dplyr::group_by(!!group_var) %>%
    dplyr::summarise(!!name := func(!!summary_var, na.rm = TRUE))
}


data %>% 
  date_diff(time2, time1) %>%  
  group_stat(Hosp, summary_var = time2_minus_time1, mean)
#> # A tibble: 2 x 2
#>   Hosp  time2_minus_time1_mean
#>   <chr>                  <dbl>
#> 1 A                       15.1
#> 2 B                       14.9

^{由 reprex软件包(v0.2.1)于2019-05-02创建 sup>}

^{Created on 2019-05-02 by the reprex package (v0.2.1)}

推荐答案

如果您打算始终以这种方式一个接一个地使用这些功能，则可以使用date_diff添加包含新列名称的属性，并使用使用该属性.在if条件下，仅当属性存在且未提供summary_var参数时才使用该属性.

If you intend to always use these functions one after another in this way you could add an attribute containing the new column's name with date_diff, and have group_stat use that attribute. With the if condition, the attribute is only used if it exists and the summary_var argument is not provided.

date_diff <- function(df, stamp1, stamp2, units = "mins"){

  stamp1 <- rlang::enquo(stamp1)
  stamp2 <- rlang::enquo(stamp2)

  name <- paste0(rlang::quo_name(stamp1), "_minus_", rlang::quo_name(stamp2))

  out <- df %>%
    dplyr::mutate(!!name := as.numeric(difftime(!!stamp1, !!stamp2, units=units)))

  attr(out, 'date_diff_nm') <- name
  out
}


group_stat <- function(df, group_var, summary_var, .f) {
  if(!is.null(attr(df, 'date_diff_nm')) & missing(summary_var))
      summary_var <- attr(df, 'date_diff_nm')

  group_var <-  rlang::enquo(group_var)
  name <- paste0(summary_var, "_", deparse(substitute(.f)))

  df %>%
    dplyr::group_by(!!group_var) %>% 
    dplyr::summarise_at(summary_var, funs(!!name := .f), na.rm = T)
}


data %>% 
  date_diff(time2, time1) %>% 
  group_stat(Hosp, .f = mean)

# # A tibble: 2 x 2
#   Hosp  time2_minus_time1_mean
#   <chr>                  <dbl>
# 1 A                       15.1
# 2 B                       14.9

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