How to combine ggplot and dplyr into a function? - r

Question

Consider this simple example
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
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.
This works:
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
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
I dont understand what is wrong here. Any ideas?
Thanks!
EDIT: interesting follow-up here how to create factor variables from quosures in functions using ggplot and dplyr?

Answer 1

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)

Answer 2

ggplot2 v3.0.0 released in July 2018 supports !! (bang bang), !!!, and :=. aes_()/aes_q() and aes_string() are soft-deprecated.
OP's original code should work
library(tidyverse)
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)
Edit: using the tidy evaluation pronoun .data[] to slice the chosen variable from the data frame also works
get_charts2 <- function(data, mygroup){
df_agg <- data %>%
group_by(.data[[mygroup]]) %>%
summarize(mean = mean(value, na.rm = TRUE),
count = n()) %>%
ungroup()
ggplot(df_agg, aes(x = count, y = mean,
color = .data[[mygroup]], group = .data[[mygroup]])) +
geom_point() +
geom_line()
}
get_charts2(dataframe, "group")
Created on 2018-04-04 by the reprex package (v0.2.0).