如何将 ggplot 和 dplyr 组合成一个函数? [英] How to combine ggplot and dplyr into a function?

问题描述

考虑这个简单的例子

library(dplyr)
library(ggplot2)

dataframe <- data_frame(id = c(1,2,3,4),
                        group = c('a','b','c','c'),
                        value = c(200,400,120,300))

# A tibble: 4 x 3
     id group value
  <dbl> <chr> <dbl>
1     1     a   200
2     2     b   400
3     3     c   120
4     4     c   300

在这里，我想编写一个函数，将数据框和分组变量作为输入.理想情况下，在分组和聚合后，我想打印一个 ggpplot 图表.

Here I want to write a function that takes the dataframe and the grouping variable as input. Ideally, after grouping and aggregating I would like to print a ggpplot chart.

这有效:

get_charts2 <- function(data, mygroup){

  quo_var <- enquo(mygroup)

  df_agg <- data %>% 
    group_by(!!quo_var) %>% 
    summarize(mean = mean(value, na.rm = TRUE),
              count = n()) %>% 
    ungroup()

  df_agg
}



> get_charts2(dataframe, group)
# A tibble: 3 x 3
  group  mean count
  <chr> <dbl> <int>
1     a   200     1
2     b   400     1
3     c   210     2

不幸的是，将 ggplot 添加到上面的函数 FAILS

Unfortunately, adding ggplot into the function above FAILS

 get_charts1 <- function(data, mygroup){

  quo_var <- enquo(mygroup)

  df_agg <- data %>% 
    group_by(!!quo_var) %>% 
    summarize(mean = mean(value, na.rm = TRUE),
              count = n()) %>% 
  ungroup()

  ggplot(df_agg, aes(x = count, y = mean, color = !!quo_var, group = !!quo_var)) + 
    geom_point() +
    geom_line() 
}


> get_charts1(dataframe, group)
Error in !quo_var : invalid argument type

我不明白这里有什么问题.有任何想法吗?谢谢！

I dont understand what is wrong here. Any ideas? Thanks!

这里有有趣的跟进如何使用 ggplot 和 dplyr 从函数中的 quosures 创建因子变量?

推荐答案

ggplot 尚不支持 tidy eval 语法(您不能使用 !!).您需要使用更传统的标准评估调用.您可以在 ggplot 中使用 aes_q 来帮助解决这个问题.

ggplot does not yet support tidy eval syntax (you can't use the !!). You need to use more traditional standard evaluation calls. You can use aes_q in ggplot to help with this.

get_charts1 <- function(data, mygroup){

  quo_var <- enquo(mygroup)

  df_agg <- data %>% 
    group_by(!!quo_var) %>% 
    summarize(mean = mean(value, na.rm = TRUE),
              count = n()) %>% 
    ungroup()

  ggplot(df_agg, aes_q(x = quote(count), y = quote(mean), color = quo_var, group = quo_var)) + 
    geom_point() +
    geom_line() 
}


get_charts1(dataframe, group)

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