```json { "action": "final", "content": "## Column Classification\n\nBased on the metadata inspection of both tables in this boxing dataset, here is the complete classification:\n\n### **Identifiers** (unique or near-unique keys)\n- `fighters.name` — fighter names (2,256 distinct values out of 2,760 rows, ~82% unique)\n\n### **Categorical Dimensions** (grouping/filtering attributes)\n- `fighters.stance` — boxing stance (3 distinct: Orthodox, Southpaw, Unknown)\n- `popular_matches.opponent_1` — first fighter in match (134 distinct)\n- `popular_matches.opponent_2` — second fighter in match (67 distinct)\n- `popular_matches.verdict` — match outcome description (102 distinct)\n\n### **Numeric Metrics** (quantitative measures)\n\n**Fighter statistics (fighters table):**\n- `wins` — career wins (0-262)\n- `looses` — career losses (0-190)\n- `draws` — career draws (0-60)\n- `ko_rate` — knockout rate percentage (stored as VARCHAR: \"0%\" to \"95.8%\")\n- `age` — fighter age (stored as VARCHAR, includes \"Unknown\")\n\n**Match statistics (popular_matches table):**\n- `opponent_1_estimated_punch_power` — punch power score (0-89)\n- `opponent_2_estimated_punch_power` — punch power score (0-89)\n- `opponent_1_estimated_punch_resistance` — resistance score (0.0-73.9, 2 nulls)\n- `opponent_2_estimated_punch_resistance` — resistance score (0.0-73.4, 8 nulls)\n- `opponent_1_estimated_ability_to_take_punch` — durability score (0-86, 1 null)\n- `opponent_2_estimated_ability_to_take_punch` — durability score (0-89, 7 nulls)\n- `opponent_1_rounds_boxed` — total rounds fought (0-462)\n- `opponent_2_rounds_boxed` — total rounds fought (0-391, 27 nulls)\n- `opponent_1_round_ko_percentage` — KO rate per round (0.0-100.0%, 24 nulls)\n- `opponent_2_round_ko_percentage` — KO rate per round (0.0-100.0%, 18 nulls)\n- `opponent_1_has_been_ko_percentage` — rate of being KO'd (0.0-62.5%, 17 nulls)\n- `opponent_2_has_been_ko_percentage` — rate of being KO'd (0.0-25.0%, 55 nulls)\n- `opponent_1_avg_weight` — average weight (0.0-432.86, 1 null)\n- `opponent_2_avg_weight` — average weight (0.0-661.5, 12 nulls)\n\n### **Dates/Times** (temporal columns)\n- `popular_matches.date` — match date (VARCHAR format, 124 distinct dates from \"1 December 2018\" to \"9 November 2019\")\n\n### **Spatial/Geographic**\n- `fighters.country` — fighter's country (107 distinct, though data quality issues evident)\n- `popular_matches.place` — match location (only \"Unknown\" values)\n\n### **Problematic Columns** (data quality issues)\n- `fighters.height` — appears to contain dates (\"13 Dec 1916\") instead of heights\n- `fighters.reach` — contains mixed formats (\"5.91 ft (1.80 m)\") and \"Unknown\"\n- `fighters.country` — contains measurements (\"75.20 inches (191 cm)\") mixed with country names\n\n### **Metadata Columns** (system-generated)\n- `_ingestion_timestamp` — data load timestamp\n- `_batch_id` — ingestion batch identifier\n- `_source_file` — source file path\n- `_source_system` — source system (\"api\")\n\n**Note:** Several columns that should be numeric (ko_rate, age, height, reach) are stored as VARCHAR and contain inconsistent formats or \"Unknown\" values, requiring cleaning before numerical analysis." } ```