```json { "action": "final", "content": "## Dataset Columns and Meanings\n\nThis dataset contains two tables tracking ITTF (International Table Tennis Federation) rankings over time. Both tables share the same 15-column structure:\n\n### Core Ranking Columns\n\n- **Rank** (BIGINT) — The player's current ranking position (0-1791 for men, 0-1379 for women)\n- **Previous** (DOUBLE) — The player's previous ranking position; nullable (380 nulls in men's, 202 in women's)\n- **Points** (BIGINT) — Current ranking points (0-17,915)\n- **Previous Points** (DOUBLE) — Ranking points from the previous period; nullable\n\n### Player Identification\n\n- **ID** (BIGINT) — Unique player identifier (100001-146254 for men, 100006-146166 for women)\n- **Name** (VARCHAR) — Player's full name (~5,429 distinct men, ~4,212 distinct women)\n- **Assoc** (VARCHAR) — Player's national association/country code (~171 countries for men, ~157 for women)\n- **Gender** (VARCHAR) — Gender category (3 distinct values across both tables)\n\n### Time Dimensions\n\n- **YearNum** (BIGINT) — Year of the ranking (2001-2020)\n- **MonthNum** (BIGINT) — Month number (0-12)\n- **WeekNum** (BIGINT) — Week number within the year (0-49)\n\nThese three temporal columns allow tracking rankings at weekly, monthly, and yearly granularity.\n\n### Metadata Columns\n\n- **_ingestion_timestamp** (TIMESTAMP) — When the data was loaded into the system\n- **_batch_id** (VARCHAR) — Identifier for the data ingestion batch\n- **_source_file** (VARCHAR) — Original CSV file path\n- **_source_system** (VARCHAR) — Source system identifier (\"api\")\n\n### Key Differences Between Tables\n\n- **ittf_rankings**: 271,271 rows, ~8,289 unique players, ~2,054 distinct rank positions\n- **ittf_rankings_women**: 202,311 rows, ~3,950 unique players, ~1,752 distinct rank positions\n\nThe women's table has Assoc marked as a spatial dimension (country-based analysis), while in the men's table it's a standard dimension." } ```