Bang-bang!!

Programmeren met dplyr

Dr. Chester Ismay

Educator, Data Scientist, and R/Python Consultant

Curly-curly ontrafeld

grouped_mean_gov_revenue <- function(group_col) {
  joined %>% 
    group_by({{ group_col }}) %>% 
    summarize(mean_gov_revenue = mean(gov_revenue_as_perc_gdp))
}
grouped_mean_gov_revenue(group_col = continent)

{{ }}

  • Forceert functieargument
  • Defuseert functieargument
Programmeren met dplyr

Bang-bang-enquo forceert en defuseert

!!enquo() is hetzelfde als {{ }}

grouped_mean_gov_revenue <- function(group_col) {
  joined %>% 
    group_by(!!enquo(group_col)) %>% 
    summarize(
      mean_gov_revenue = mean(
        gov_revenue_as_perc_gdp
      )
   )
}
grouped_mean_gov_revenue(group_col = continent)
# A tibble: 17 × 2
    year mean_gov_revenue
   <dbl>            <dbl>
 1  2000             39.4
 2  2001             30.8
...
16  2015             34.7
17  2016             32.3
Programmeren met dplyr

Meerdere functieargumenten

grouped_mean_gov_revenue <- function(group_col) {
  joined %>% 
    group_by(!!enquo(group_col)) %>% 
    summarize(mean_gov_revenue = mean(gov_revenue_as_perc_gdp))
}
grouped_mean_for_column <- function(group_col, col_to_mean) {

joined %>% group_by(!!enquo(group_col)) %>%
summarize(mean(!!enquo(col_to_mean))) }
Programmeren met dplyr

grouped_mean_for_column() aanroepen

grouped_mean_for_column(group_col = continent,
                        col_to_mean = perc_cvd_crd_70)
# A tibble: 5 × 2
  continent `mean(perc_cvd_crd_70)`
  <fct>                       <dbl>
1 Africa                      23.8 
2 Americas                    14.7 
3 Asia                        19.8 
4 Europe                      16.3 
5 Oceania                      9.91
Programmeren met dplyr

Laten we oefenen!

Programmeren met dplyr

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