#TIDYVERSE SUMMARIZE HOW TO#
#TIDYVERSE SUMMARIZE UPDATE#

What if I want to divide my students into two groups, one if their student_id is even, another if their student_id is odd? group_by allows me to pass in a function of column names, from which it will derive a grouping. Summarize_student_performance(assignment_id, question_number)Įnquo(s): summarize_student_performance grouped by functions of parameters Let’s see how that looks: summarize_student_performance %ĭplyr::group_by(!!!rlang::ensyms(.)) %>% Since we might have more than one parameter to look at, we use the rlang function ensyms rather than ensym, and !!! (pronounced “bang-bang-bang” with formal meaning “ungroup and splice,” but just remember that !!! is connected to. , which is used in R functions to indicate a list of parameters.

data and a single parameter, our function will accept.

#TIDYVERSE SUMMARIZE UPDATE#

Let’s update summarize_student_performance to accept any number of grouping columns. Looking at that data, what I’d really like to do is group by both question_number and assignment_id, so I can see how students performed question-by-question on each assignment. Summarize_student_performance(question_number)Įnsyms and !!!: summarize_student_performance with multiple grouping parameters Mean_requested_solution = mean(requested_solution) With those two functions in place, we get this: summarize_student_performance %ĭplyr::group_by(!!rlang::ensym(group_col)) %>% I think of !! as telling group_by “It’s not group_col, but it’s also not not group_col.” Then we’ll tell group_by to process the code we gave it rather than looking for a column named “rlang::ensym(group_col)” with !!, !!rlang::ensym(group_col). First we tell our function “think of this parameter as a symbol” using the ensym function, rlang::ensym(group_col). To do this, we need two functions from rlang: ensym and !! (pronounced “bang-bang”). I need to tell it to translate the parameter I send in to the name of a column. The problem is, group_by already expects a “bare” symbol naming that column if I tell it to group_by(group_col), it will look for a column named “group_col” in the data, fail to find that column, and throw an error.

#TIDYVERSE SUMMARIZE HOW TO#

In my function, I want to pass in a parameter telling the function how to group the data.

Tidyverse summarize