```json { "action": "final", "content": "Here is a representative sample of 10 rows from the dataset, which has been rendered for you to explore.\n\nThe dataset captures individual users' late-night phone habits and their resulting sleep metrics. Key dimensions include:\n\n* **Demographics & Lifestyle:** `age`, `gender`, `occupation_type`, `caffeine_post_5pm_mg`, and `physical_activity_min`.\n* **Screen Time Habits:** `bedtime_phone_minutes`, `primary_bedtime_app`, `screen_brightness_pct`, and whether a `blue_light_filter_active` is used.\n* **Sleep Outcomes:** `total_sleep_hours`, `sleep_latency_min` (how long it takes to fall asleep), `deep_sleep_pct`, `rem_sleep_pct`, `morning_alarm_snoozes`, `next_day_fatigue_score`, and the overall `sleep_debt_category`.\n\nFor example, the sample includes a 29-year-old female healthcare worker (USR-00001) who spent 179 minutes on Instagram/Reddit before bed and experienced a high sleep latency of 84.4 minutes, resulting in \"Severe Sleep Debt\". In contrast, a 36-year-old male freelancer (USR-00009) who spent 65 minutes reading the news with a blue light filter active achieved 8.0 hours of sleep and \"Optimal Recovery\"." } ```