Sports League Standings (CSV)
A football-style league table — position, played, won/drawn/lost, goals for/against, goal difference, and points for ten teams, derived from a full round of synthetic match results. Paired with the results JSON.
position,team,played,won,drawn,lost,gf,ga,gd,points
1,Silver Sharks,9,5,2,2,21,14,7,17
2,Gold Eagles,9,4,3,2,21,21,0,15
3,Red Lions,9,4,2,3,22,17,5,14
4,Black Bears,9,4,1,4,22,19,3,13
5,Blue Hawks,9,4,1,4,19,22,-3,13
6,White Tigers,9,3,3,3,14,17,-3,12
7,Orange Foxes,9,3,2,4,18,20,-2,11
8,Teal Rays,9,3,1,5,20,20,0,10
9,Purple Dragons,9,2,4,3,16,20,-4,10
10,Green Wolves,9,2,3,4,14,17,-3,9
Specifications
- Teams
- 10
- Schema
- position, team, played, won, drawn, lost, gf, ga, gd, points
- Note
- derived from the match results
- Domain
- sports
What is a .csv file?
CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.
How to use this file
Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.
Code examples
import pandas as pd
df = pd.read_csv("standings.csv")
print(df.head())
print(df.dtypes)Related files
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Generated by generation/data_domains.py. Free for any use, no attribution required — license.