Row-binding future_map results

You work for a higher studies consultancy which recommends US universities to applicants abroad. You have sourced a university ranking dataset which contains a column score for research, citations, etc, for different universities.

The team statistician has written a function, calc_quants(), that is available to you. This function calculates a range for the scores of a given university. It takes two arguments, 1) a data frame with the column score, and 2) the quantile values of interest q_values. The quantiles of interest are available to you as the variable my_q_values.

my_q_values <- c(0.025, 0.975)

You are asked to apply this function to the data for each university in parallel.

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Este ejercicio forma parte del curso

Parallel Programming in R

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Instrucciones del ejercicio

Create a configuration that specifies my_q_values as a global variable required by all workers.
Split the data frame uni_data by university_name.
Apply calc_quants() to each university's scores using the correct future_map() variant to bind results by rows.
Specify the values for the q_values and configuration for .options.

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plan(cluster, workers = 6)

# Create a configuration object to export global variables
config <- ___(___ = ___)

uni_data %>%
  # Split the data frame
  ___(___) %>% 
  # Specify the future_map variant and the function to map
  ___(___,
  # Specify values for the q_values argument and configuration for .options
                 q_values = ___,
                 .options = ___,
                 .id = "university")
plan(sequential)

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