Extra Credit Assignment

# Load necessary libraries
library(readxl)

# Load the movie ratings data from Excel file
file_path <- "/Users/aribarazzaq/Downloads/MovieRatings (1).xlsx"

# Load the MovieRatings and Global Baseline sheets
movie_ratings <- read_excel(file_path, sheet = "MovieRatings")
global_baseline <- read_excel(file_path, sheet = "Global Baseline")

# View the structure of the MovieRatings dataset
head(movie_ratings)

## # A tibble: 6 × 7
##   Critic   CaptainAmerica Deadpool Frozen JungleBook PitchPerfect2 StarWarsForce
##   <chr>             <dbl>    <dbl>  <dbl>      <dbl>         <dbl>         <dbl>
## 1 Burton               NA       NA     NA          4            NA             4
## 2 Charley               4        5      4          3             2             3
## 3 Dan                  NA        5     NA         NA            NA             5
## 4 Dieudon…              5        4     NA         NA            NA             5
## 5 Matt                  4       NA      2         NA             2             5
## 6 Mauricio              4       NA      3          3             4            NA

# Calculate the global average rating across all movies and critics
ratings <- movie_ratings[, -1]  # Exclude the 'Critic' column
all_ratings <- as.numeric(unlist(ratings))
global_average <- mean(all_ratings, na.rm = TRUE)

# Calculate movie-specific biases
movie_biases <- colMeans(ratings, na.rm = TRUE) - global_average

# Calculate critic-specific biases
critic_biases <- rowMeans(ratings, na.rm = TRUE) - global_average

# Create a Global Baseline Estimate recommendation function
recommend_movie <- function(critic_name, movie_name) {
  # Find the critic row and movie column
  critic_index <- which(movie_ratings$Critic == critic_name)
  movie_index <- which(names(movie_ratings) == movie_name)
  
  # Get the critic and movie bias
  critic_bias <- critic_biases[critic_index]
  movie_bias <- movie_biases[movie_index - 1]  # Adjust for 'Critic' column
  
  # Calculate the Global Baseline Estimate
  global_baseline_estimate <- global_average + critic_bias + movie_bias
  
  return(global_baseline_estimate)
}

# Example usage: recommend a movie for Charley
recommend_movie("Charley", "Deadpool")

## Deadpool 
## 4.010018