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from datasets import Dataset, DatasetBuilder, DatasetInfo, Features, Value, SplitGenerator
import pandas as pd
class Euro2020Dataset(DatasetBuilder):
VERSION = "1.0.0"
def _info(self):
return DatasetInfo(
description="Your dataset description here.",
features=Features({
"HomeTeamName": Value("string"),
"AwayTeamName": Value("string"),
"DateandTimeCET": Value("string"),
"MatchID": Value("int64"),
"RoundName": Value("string"),
"Stage": Value("string"),
"MatchDay": Value("int64"),
"Session": Value("int64"),
"MatchMinute": Value("int64"),
"InjuryTime": Value("int64"),
"NumberofPhases": Value("int64"),
"Phase": Value("int64"),
"ScoreHome": Value("int64"),
"ScoreAway": Value("int64"),
"MatchStatus": Value("string"),
"StadiumID": Value("int64"),
"NumberofMatchesRefereedPostMatch": Value("int64"),
"TotalNumberofMatchesRefereed": Value("int64"),
"NumberofMatchesRefereedinGroupStage": Value("int64"),
"NumberofMatchesRefereedinKnockoutStage": Value("int64"),
"AssistantRefereeWebName": Value("string"),
"Humidity": Value("int64"),
"Temperature": Value("int64"),
"WindSpeed": Value("int64"),
"MatchEvent": Features({
"1-First Half": Features({
"Event": Value("string"),
"Minute": Value("int"),
"Phase": Value("int"),
"InjuryMinute": Value("int"),
"TeamFromID": Value("float"),
"TeamToID": Value("float"),
"PlayerFromID": Value("float"),
"PlayerToID": Value("float"),
"Time": Value("string"),
"MatchEventAttribute": Value("float"),
}),
"2-Second Half": Features({
"Event": Value("string"),
"Minute": Value("int"),
"Phase": Value("int"),
"InjuryMinute": Value("int"),
"TeamFromID": Value("float"),
"TeamToID": Value("float"),
"PlayerFromID": Value("float"),
"PlayerToID": Value("float"),
"Time": Value("string"),
"MatchEventAttribute": Value("float"),
}),
"3-Extra Time First Half": Features({
"Event": Value("string"),
"Minute": Value("int"),
"Phase": Value("int"),
"InjuryMinute": Value("int"),
"TeamFromID": Value("float"),
"TeamToID": Value("float"),
"PlayerFromID": Value("float"),
"PlayerToID": Value("float"),
"Time": Value("string"),
"MatchEventAttribute": Value("float"),
}),
"4-Extra Time Second Half": Features({
"Event": Value("string"),
"Minute": Value("int"),
"Phase": Value("int"),
"InjuryMinute": Value("int"),
"TeamFromID": Value("float"),
"TeamToID": Value("float"),
"PlayerFromID": Value("float"),
"PlayerToID": Value("float"),
"Time": Value("string"),
"MatchEventAttribute": Value("float"),
}),
"5-Penalty Shootout": Features({
"Event": Value("string"),
"Minute": Value("int"),
"Phase": Value("int"),
"InjuryMinute": Value("int"),
"TeamFromID": Value("float"),
"TeamToID": Value("float"),
"PlayerFromID": Value("float"),
"PlayerToID": Value("float"),
"Time": Value("string"),
"MatchEventAttribute": Value("float"),
}),
}),
"TeamLineUps": Value("dict"),
"TeamStats": Value("dict"),
"PlayerStats": Value("dict"),
"PlayerPreMatchInfo": Value("dict"),
}),
supervised_keys=None,
homepage="Optional dataset homepage",
license= "",
citation="Optional citation"
)
def _split_generators(self, dl_manager):
# Since the final processed dataset is a single CSV file that combines the content from numerous rows to only 51 rows,
# with each row representing the information of each game, I will just use a single 'train' split and no need for test / validation.
path = "/Users/chuhanguo/Desktop/Winter 2024/STA 663/Euro2020.csv"
return [
SplitGenerator(
name="train",
gen_kwargs={"filepath": path}
),
]
def _generate_examples(self, path):
data = pd.read_csv(path)
for idx, row in data.iterrows():
yield idx, {
"HomeTeamName": row["HomeTeamName"],
"AwayTeamName": row["AwayTeamName"],
"DateandTimeCET": row["DateandTimeCET"],
"MatchID": row["MatchID"],
"RoundName": row["RoundName"],
"Stage": row["Stage"],
"MatchDay": row["MatchDay"],
"Session": row["Session"],
"MatchMinute": row["MatchMinute"],
"InjuryTime": row["InjuryTime"],
"NumberofPhases": row["NumberofPhases"],
"Phase": row["Phase"],
"ScoreHome": row["ScoreHome"],
"ScoreAway": row["ScoreAway"],
"MatchStatus": row["MatchStatus"],
"StadiumID": row["StadiumID"],
"NumberofMatchesRefereedPostMatch": row["NumberofMatchesRefereedPostMatch"],
"TotalNumberofMatchesRefereed": row["TotalNumberofMatchesRefereed"],
"NumberofMatchesRefereedinGroupStage": row["NumberofMatchesRefereedinGroupStage"],
"NumberofMatchesRefereedinKnockoutStage": row["NumberofMatchesRefereedinKnockoutStage"],
"AssistantRefereeWebName": row["AssistantRefereeWebName"],
"Humidity": row["Humidity"],
"Temperature": row["Temperature"],
"WindSpeed": row["WindSpeed"],
"MatchEvent": row["MatchEvent"],
"TeamLineUps": row["TeamLineUps"],
"TeamStats": row["TeamStats"],
"PlayerStats": row["PlayerStats"],
"PlayerPreMatchInfo": row["PlayerPreMatchInfo"],
}
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