I'm using mongolite in R to read a mongo collection with the following structure:

[{_id: 0, date: 20221201, dailyAnswer:[
   {question:a,score:1},
   {question:b,score:3},
   {question:c,score:2}
]},
{_id: 1, date: 20221201, dailyAnswer:[
   {question:a,score:3},
   {question:b,score:2},
   {question:c,score:1}
]},
{_id: 0, date: 20221202, dailyAnswer:[
   {question:a,score:2},
   {question:b,score:2},
   {question:c,score:3}
]},
{_id: 1, date: 20221202, dailyAnswer:[
   {question:a,score:3},
   {question:b,score:1},
   {question:c,score:1}
]}]

For each document I'd like to extract each question score into a column, with the table structure:

_id | date | question_a_score | question_b_score | question_c_score

In MongoDB Compass I've written a query to extract them:

{
q_a_score: { $arrayElemAt: [ "$dailyAnswer.score",0]},
q_b_score: { $arrayElemAt: [ "$dailyAnswer.score",1]},
q_c_score: { $arrayElemAt: [ "$dailyAnswer.score",2]}
}

Which returns:

[{
_id: 0,
question_a_score:1,
question_b_score:3,
question_c_score:2},
...,
{
_id: 1,
question_a_score:3,
question_b_score:1,
question_c_score:1}
}]

However, I'm not sure whether to use the $aggregate or $find methods in mongolite in R, and how to structure the pipeline or query arguments in those methods respectively.