
library(testthat)

source("user_code.R")
test_that("returns suggestion to optimize df1 when df1 uses more memory than df2", {
  df1 <- data.frame(id = 1:1000, name = rep(c("apple", "banana", "cherry"), length.out = 1000), stringsAsFactors = FALSE)
  df2 <- data.frame(id = 1:1000, name = factor(rep(c("apple", "banana", "cherry"), length.out = 1000)), stringsAsFactors = FALSE)
  result <- compare_memory_usage(df1, df2)
  expect_equal(result, "Consider converting character columns to factors or using more efficient data types in df1.",
               info = "Should suggest optimizing df1 when df1 uses more memory than df2.")
})

test_that("returns suggestion to optimize df2 when df2 uses more memory than df1", {
  df1 <- data.frame(id = 1:1000, name = factor(rep(c("apple", "banana", "cherry"), length.out = 1000)), stringsAsFactors = FALSE)
  df2 <- data.frame(id = 1:1000, name = rep(c("apple", "banana", "cherry"), length.out = 1000), stringsAsFactors = FALSE)
  result <- compare_memory_usage(df1, df2)
  expect_equal(result, "Consider converting character columns to factors or using more efficient data types in df2.",
               info = "Should suggest optimizing df2 when df2 uses more memory than df1.")
})

test_that("returns suggestion to review data types if both data frames use similar memory", {
  df1 <- data.frame(id = 1:10, value = rep(1, 10), stringsAsFactors = FALSE)
  df2 <- data.frame(id = 1:10, value = rep(1, 10), stringsAsFactors = FALSE)
  result <- compare_memory_usage(df1, df2)
  expect_equal(result, "Both data frames use similar memory. Review data types for further optimization.",
               info = "Should suggest reviewing data types if both data frames use similar memory.")
})

test_main.R

Master the essential R data structures used in exploratory data analysis (EDA), focusing on practical applications and hands-on challenges. This course is designed for learners already familiar with R syntax, core data structures, and data cleaning/wrangling techniques.

Explore the essential R data structures that power effective exploratory data analysis, with a focus on practical usage and hands-on challenges.

Challenge: Memory Efficiency

Oplossing