Extra Credit: You May Work In Groups But Everybody In The Gr

Extra Credityou May Work In Groups But Everybody In The Group Must Put

Extra Credit You may work in groups but everybody in the group MUST put down who they worked with! No exceptions! 1. Implement a function called RPS() which is a game of Rock, Paper, Scissor. The game will consist of you (the user) playing against the computer. The computer will obtain its values from the built-in Python randomizer (import random). The function must contain the following for full credit: 1. Accept user input to determine what the user selects (Rock, Paper, or Scissor) 2. Loop continuously until 'quit' is entered 3. If the user enters something other than ‘r’, ‘p’, or ‘s’ then they should be notified but the game should continue. 4. Keep score for both the player and CPU 5. After each turn, print out the results, what each player had selected, and the current score 6. After 'quit' is entered, print out a recap of the game including the final score and who won or if there was a tie. 2. Implement a function called topRated(). The function will take a file name as a parameter and return a sorted list. The file it reads in contains 500 numeric movie IDs and their ratings by user. The function should return a list of movie IDs and their average rating based on the file data. The list that is returned should also be sorted by average rating. I have included code in the extra credit template to do that for you. HINT: The best way to tackle this problem is to break it up into two parts. You must first read the file in and create a dictionary of all the movie IDs as keys. The value to those keys should be a list. Worry about solving the average after the dictionary is created. 3. What good are movie IDs and ratings? You want to know the actual title of the movie! Implement a function called getTitles(). The function takes two parameters. The first is the list we created in the previous problem. The second is a text file containing movie IDs and titles. The function should loop through the list of IDs that is passed to it and through the text file. When an ID in the list matches that of an ID in the text file, you know the title in the text file is associated with that ID. Return a sorted list by average rating. I have included code in the extra credit template to do that for you.

Paper For Above instruction

In this assignment, three primary Python programming tasks are outlined, each aimed at developing different skills, from game implementation to data processing and file handling. These tasks are interconnected and build upon one another, providing a comprehensive exercise in Python programming, particularly emphasizing control flow, data structures, and file I/O operations.

The first task requires implementing the classic game of Rock, Paper, Scissor (RPS) through a function called RPS(). This function engages the user in an interactive loop where they can continuously input their choice among rock, paper, or scissors, represented by 'r', 'p', or 's'. The computer opponent's choice is generated randomly using Python's built-in random module, ensuring unpredictability in each round. The game should validate user input, providing an alert if an invalid choice is entered, and continue prompting the user without terminating. Scores for both the user and the computer must be tracked dynamically and displayed after each turn, including the choices made and current scores. When the user enters 'quit', the game concludes and presents a final recap, summarizing the total scores and declaring a winner or a tie, providing closure to the game session.

The second task involves processing a dataset file containing 500 movie IDs and their associated user ratings. The goal is to develop a function called topRated() that reads this file, builds a dictionary with movie IDs as keys and lists of ratings as values. After populating this data structure, the function computes the average rating for each movie, sorts the movies based on their average ratings, and returns this sorted list. This process demonstrates effective data gathering and manipulation, emphasizing the importance of organizing raw data for meaningful analysis. It encourages the breakdown of complex tasks into smaller steps—reading the file, creating data structures, calculating averages, and sorting results.

The third task enhances the data interpretation by linking movie IDs to their actual titles. The getTitles() function takes the sorted list of movies with their average ratings and a text file containing movie IDs paired with titles. It cross-references each ID from the list against entries in the text file, matching IDs to obtain the corresponding movie titles. The resulting list, sorted by average ratings, includes human-readable titles rather than raw IDs, providing valuable context for understanding the data. This step underscores the significance of integrating multiple data sources and performing lookups to enrich information, which is a common requirement in data analysis and programming projects.

Collectively, these tasks reinforce essential programming concepts: creating interactive applications, managing and processing datasets, implementing robust input validation, and integrating data from multiple sources. By completing them, a Python programmer gains practical experience in control structures, data organization, file handling, and user interaction—skills fundamental to more advanced data manipulation and software development projects.

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