Question

我正在尝试通过代码为“ summaryize + group”创建一个函数。这是我正在处理的数据集。包括ID，国家/地区，苹果，橘子，波罗蜜，香蕉的列（如果该人喜欢此水果，则== 1；如果不喜欢此水果，则== 0）

这是我正在使用的功能代码：

summarize_pct<-function(x,y){
  sample %>%
    group_by(x, y) %>%
    dplyr::summarise(perc = n()) %>%
    mutate(Apple = c("dislike", "like")[y + 1])  %>%
    tidyr::spread(y, perc, fill = 0) %>%
    ungroup() %>%
    mutate_at(vars(dislike, like), ~./sum(.))
return(summary)
}
summarize_pct(Country,Apple)

但是我收到了错误消息。...

这是我正在处理的数据：

structure(list(id = 1:30, Country = c("USA", "USA", "USA", "USA", 
"USA", "USA", "USA", "USA", "Germany", "Germany", "Germany", 
"Germany", "Germany", "Germany", "UK", "UK", "UK", "UK", "UK", 
"UK", "UK", "UK", "UK", "UK", "France", "France", "France", "France", 
"France", "France"), Apple = c(1L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 
1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 
1L, 1L, 1L, 1L, 1L, 1L), Banana = c(1L, 1L, 0L, 1L, 1L, 0L, 0L, 
1L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 
1L, 1L, 0L, 0L, 0L, 1L, 1L), Orange = c(0L, 0L, 0L, 0L, 0L, 1L, 
1L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 
1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L), Jackfruit = c(0L, 0L, 1L, 1L, 
0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 
1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L)), row.names = c(NA, -30L
), class = c("tbl_df", "tbl", "data.frame"))

Answer 1

如果要将其用作功能，则可能需要使用非标准评估。从Rlang 0.4.0开始使用curl-curly运算符

library(dplyr)
library(rlang)

summarize_pct<-function(df, x , y) {
    df %>%
     group_by({{x}}, {{y}}) %>%
     dplyr::summarise(perc = n()) %>%
     mutate(temp_name = c("dislike", "like")[{{y}} + 1])  %>%
     select(-{{y}}) %>%
     tidyr::spread(temp_name, perc, fill = 0) %>%
     ungroup() %>%
     mutate_at(vars(dislike, like), ~./sum(.))
}

summarize_pct(sample, Country,Apple)
# A tibble: 4 x 3
#  Country dislike  like
#  <chr>     <dbl> <dbl>
#1 France    0     0.353
#2 Germany   0.308 0.118
#3 UK        0.462 0.235
#4 USA       0.231 0.294

summarize_pct(sample, Country,Orange)
# A tibble: 4 x 3
#  Country dislike  like
#  <chr>     <dbl> <dbl>
#1 France    0.2   0.2  
#2 Germany   0.133 0.267
#3 UK        0.267 0.4  
#4 USA       0.4   0.133

创建一个关于summary + group by的函数

1 个答案: