Identify country with highest sunny-day probability

Write SQL to find the country with the highest probability that a day is sunny. Use the schema and sample data below. Rules: consider a day sunny for a country if any observation for that country on that date has condition = 'Sunny' (case-insensitive); exclude dates where all observations for that country are NULL; compute probability = sunny_days / total_observed_days; only include countries with at least 5 observed days; tie-break by (1) higher probability, (2) higher total_observed_days, then (3) country_name ascending; return one row with columns (country_name, sunny_days, total_days, sunny_day_prob rounded to 3 decimals). Schema:

• countries(country_id INT PRIMARY KEY, country_name VARCHAR)
• weather_obs(obs_id INT PRIMARY KEY, country_id INT, obs_date DATE, condition VARCHAR, temp_c INT) Sample data (ASCII): Table: countries +------------+--------------+ | country_id | country_name | +------------+--------------+ | 1 | USA | | 2 | Canada | | 3 | Japan | +------------+--------------+ Table: weather_obs +--------+------------+------------+-----------+--------+ | obs_id | country_id | obs_date | condition | temp_c | +--------+------------+------------+-----------+--------+ | 1 | 1 | 2025-06-01 | Sunny | 30 | | 2 | 1 | 2025-06-02 | Cloudy | 24 | | 3 | 1 | 2025-06-03 | sunny | 28 | | 4 | 1 | 2025-06-03 | Rain | 22 | | 5 | 2 | 2025-06-01 | Rain | 18 | | 6 | 2 | 2025-06-02 | Sunny | 21 | | 7 | 2 | 2025-06-02 | Cloudy | 20 | | 8 | 2 | 2025-06-03 | NULL | 19 | | 9 | 2 | 2025-06-04 | Sunny | 23 | | 10 | 3 | 2025-06-01 | Cloudy | 25 | | 11 | 3 | 2025-06-02 | Sunny | 27 | | 12 | 3 | 2025-06-03 | Sunny | 29 | | 13 | 3 | 2025-06-04 | NULL | 26 | | 14 | 1 | 2025-06-04 | Sunny | 31 | | 15 | 2 | 2025-06-05 | Sunny | 24 | | 16 | 3 | 2025-06-05 | Rain | 22 | +--------+------------+------------+-----------+--------+ Write a single SQL query (standard SQL) that implements the rules above and returns the required row.