r - grouped_df_impl 中的错误(数据，取消命名(vars)，删除): Column is unknown

Question

我有一个看起来像这样的数据框

df <- data.frame (
  age = rep(c("40-44", "45-49", "50-54", "55-59", "60-64"),4),
  dep = rep(c("Dep1", "Dep2", "Dep3", "Dep4", "Dep5"),4),
  ethnic = rep(c(rep("M",5),rep("NM",5)),2),
  gender = c(rep("M",10), rep("F",10))
)

我正在尝试为许多相似的数据框生成描述性统计信息，所有这些数据框都来自不同的来源，因此我可以进行比较。

我正在运行以下代码来获取性别、性别、种族、年龄和性别 + 种族的计数和比例作为函数，我可以将其应用于多个数据集

Dems_fun <- function(data, sex, eth, dep, age) {

  Fun <- function(data, ...) {
    group_var <- quos(...)

    data %>% 
      group_by(!!! group_var) %>%
      summarise (n = n()) %>%
      mutate(freq = n / sum(n)) %>%
      unite(dem, !!! group_var, sep = "_", remove = T)
  }

  Sex <- Fun(data, sex)
  Sex_eth <- Fun(data, sex, eth) 
  Eth <- Fun(data, eth)
  Dep <- Fun(data, dep)
  Age <- Fun(data, age)

  Dems <- rbind(Sex, Sex_eth, Eth, Dep, Age)
  colnames(Dems) <- c("Category", "count", "percentage")
  return(Dems)
}

当我运行这个函数时

test <- Dems_fun(df, gender, ethnic, dep, age)

我收到以下错误消息:

Error in grouped_df_impl(data, unname(vars), drop) : Column sex is unknown

谁能告诉我哪里出错了？

我看过类似的问题Error with using enquo for creating function with ddplyr ，但我无法判断是否同样的错误适用于我的示例。

Answer 1

您唯一缺少的是您需要 enquo函数的列名，然后在稍后将它们用作函数参数时取消引用( !! )它们。所以你会做age_var <- enquo(age)然后用 !!age_var 返回引用当你调用Fun .

library(tidyverse)

df <- data.frame (
  age = rep(c("40-44", "45-49", "50-54", "55-59", "60-64"),4),
  dep = rep(c("Dep1", "Dep2", "Dep3", "Dep4", "Dep5"),4),
  ethnic = rep(c(rep("M",5),rep("NM",5)),2),
  gender = c(rep("M",10), rep("F",10))
)

Dems_fun <- function(data, sex, eth, dep, age) {
  # enquo all these variables
  sex_var <- enquo(sex)
  eth_var <- enquo(eth)
  dep_var <- enquo(dep)
  age_var <- enquo(age)

  Fun <- function(data, ...) {
    group_var <- quos(...)

    data %>% 
      group_by(!!! group_var) %>%
      summarise (n = n()) %>%
      mutate(freq = n / sum(n)) %>%
      unite(dem, !!! group_var, sep = "_", remove = T)
  }

  # unquote all these variables
  Sex <- Fun(data, !!sex_var)
  Sex_eth <- Fun(data, !!sex_var, !!eth_var) 
  Eth <- Fun(data, !!eth_var)
  Dep <- Fun(data, !!dep_var)
  Age <- Fun(data, !!age_var)

  Dems <- rbind(Sex, Sex_eth, Eth, Dep, Age)
  colnames(Dems) <- c("Category", "count", "percentage")
  return(Dems)
}

Dems_fun(df, gender, ethnic, dep, age)
#> # A tibble: 18 x 3
#>    Category count percentage
#>    <chr>    <int>      <dbl>
#>  1 F           10        0.5
#>  2 M           10        0.5
#>  3 F_M          5        0.5
#>  4 F_NM         5        0.5
#>  5 M_M          5        0.5
#>  6 M_NM         5        0.5
#>  7 M           10        0.5
#>  8 NM          10        0.5
#>  9 Dep1         4        0.2
#> 10 Dep2         4        0.2
#> 11 Dep3         4        0.2
#> 12 Dep4         4        0.2
#> 13 Dep5         4        0.2
#> 14 40-44        4        0.2
#> 15 45-49        4        0.2
#> 16 50-54        4        0.2
#> 17 55-59        4        0.2
#> 18 60-64        4        0.2

由 reprex package 创建于 2018-05-30 (v0.2.0).