User Engagement Pattern Classification

Classify each viewing session as Abandoned / Sampled / Completed by watched percentage, find each user's most-common pattern, and return a count of users per dominant pattern. User Engagement Analysis You need to analyze how users interact with video content. We categorize a user's activity based on the percentage of the video they watched: "Abandoned": The user watched less than 25% of the content. "Sampled": The user watched between 25% and 75% (inclusive). "Completed": The user watched more than 75% of the content. Data Format You have a list of viewing sessions. Each session contains these details: account_id: The user's ID. title_id: The content ID. title_runtime_secs: The total length of the video in seconds. watched_secs: How many seconds the user actually watched. day_nbr: The day the viewing happened (ignore this for this problem). The Goal Write a function that does the following: Classify Sessions: Label every session as "Abandoned", "Sampled", or "Completed". Find User Habits: For each user, identify their most common engagement pattern. Note: If there is a tie (two patterns appear the same amount of times), you can pick any of the tied patterns. Count Totals: Return a dictionary/object showing the count of users for each dominant pattern. Example Walkthrough Input: viewing_data = [ {"account_id": "U1", "title_id": "T1", "title_runtime_secs": 3600, "watched_secs": 3500, "day_nbr": 1}, {"account_id": "U1", "title_id": "T2", "title_runtime_secs": 5400, "watched_secs": 5000, "day_nbr": 3}, {"account_id": "U2", "title_id": "T1", "title_runtime_secs": 3600, "watched_secs": 800, "day_nbr": 5}, {"account_id": "U2", "title_id": "T2", "title_runtime_secs": 2700, "watched_secs": 500, "day_nbr": 9}, {"account_id": "U3", "title_id": "T1", "title_runtime_secs": 3600, "watched_secs": 1800, "day_nbr": 2} ] Output: {"Completed": 1, "Abandoned": 1, "Sampled": 1} Explanation: User U1: Watched 97% (3500/3600) -> Completed Watched 93% (5000/5400) -> Completed Main Pattern: Completed User U2: Watched 22% (800/3600) -> Abandoned Watched 19% (500/2700) -> Abandoned Main Pattern: Abandoned User U3: Watched 50% (1800/3600) -> Sampled Main Pattern: Sampled Result: 1 user is "Completed", 1 is "Abandoned", and 1 is "Sampled". Input Constraints 1 <= viewing_data.length <= 10^5 1 <= title_runtime_secs <= 10^6 0 <= watched_secs <= title_runtime_secs account_id and title_id are always non-empty strings.