Load yearly CSV snapshots
readyLoaded 144323 rows from the yearly FIFA CSV snapshots into one unified table.
Usage Scenario 1
Data loading and cleaning
Inspect the unified FIFA archive, verify schema coverage, and track the cleaning rules that prepare the player snapshot table for downstream analysis.
Source: csv-archive. Preview rows are sampled from the current player snapshot view.
Rows
144.3K
Columns
110
Seasons
15, 16, 17, 18, 19, 20, 21, 22
Position fields
27
Tidy player snapshot cache
Archive inspection
Preview rows and column profile
| sofifa_id | short_name | player_positions | overall | potential | value_eur | wage_eur | league_name | nationality_name | season | gender |
|---|---|---|---|---|---|---|---|---|---|---|
| 226324 | C. Lloyd | CM, CAM, LM, ST | 91 | 91 | null | null | null | United States | 16 | female |
| 226328 | M. Rapinoe | LM, CM | 90 | 90 | null | null | null | United States | 16 | female |
| 226334 | A. Wambach | ST | 90 | 90 | null | null | null | United States | 16 | female |
| 226362 | L. Nécib | LM, CAM | 90 | 90 | null | null | null | France | 16 | female |
| 226373 | N. Keßler | CM | 89 | 89 | null | null | null | Germany | 16 | female |
Cleaning checklist
Data preparation status
Normalize numeric market fields
readyConverted ratings, IDs, value_eur, wage_eur, release_clause_eur, and ability columns into nullable numeric types.
Split position rating strings
readyParsed 27 position columns into base, modifier, and effective rating fields.
Write tidy parquet cache
readyParquet cache written successfully.
Null hotspots
Columns requiring special handling
club_loaned_from
94%Post-cleaning null rate from the generated tidy dataset.
nation_team_id
93%Post-cleaning null rate from the generated tidy dataset.
nation_position
93%Post-cleaning null rate from the generated tidy dataset.
nation_jersey_number
93%Post-cleaning null rate from the generated tidy dataset.
nation_logo_url
93%Post-cleaning null rate from the generated tidy dataset.