ForzaJuve1
commited on
Commit
•
f4e82a4
1
Parent(s):
42b61e0
Update Integration.py
Browse files- Integration.py +39 -35
Integration.py
CHANGED
@@ -553,6 +553,10 @@ class Euro2020Dataset(GeneratorBasedBuilder):
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#csv.field_size_limit(sys.maxsize)
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def _generate_examples(self, filepath):
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#table = pq.read_table(filepath)
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#df = table.to_pandas()
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#df = pd.read_parquet(filepath)
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@@ -561,9 +565,9 @@ class Euro2020Dataset(GeneratorBasedBuilder):
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#'row' is a Pandas Series object representing the row data
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#Directly yield the id and row.to_dict() if the DataFrame structure matches the desired output
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#yield id, row.to_dict()
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with open(filepath, encoding="utf-8") as f:
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reader = pd.read_parquet(f)
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for id, row in enumerate(reader):
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#match_event_str = row["MatchEvent"]
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#match_event_replaced = match_event_str.replace("'", '"')
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@@ -590,36 +594,36 @@ class Euro2020Dataset(GeneratorBasedBuilder):
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#pre_match_replaced = pre_match_replaced.replace(": nan", ": null")
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#pre_match_info = yaml.safe_load(pre_match_str)
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yield id, {
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"HomeTeamName": row["HomeTeamName"],
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"AwayTeamName": row["AwayTeamName"],
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"DateandTimeCET": row["DateandTimeCET"],
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"MatchID": row["MatchID"],
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"RoundName": row["RoundName"],
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"Stage": row["Stage"],
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"MatchDay": row["MatchDay"],
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"Session": row["Session"],
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"MatchMinute": row["MatchMinute"],
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"InjuryTime": row["InjuryTime"],
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"NumberOfPhases": row["NumberOfPhases"],
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"Phase": row["Phase"],
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"ScoreHome": row["ScoreHome"],
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"ScoreAway": row["ScoreAway"],
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"MatchStatus": row["MatchStatus"],
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"StadiumID": row["StadiumID"],
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"RefereeWebName": row["RefereeWebName"],
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"NumberofMatchesRefereedPostMatch": row["NumberofMatchesRefereedPostMatch"],
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"TotalNumberofMatchesRefereed": row["TotalNumberofMatchesRefereed"],
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"NumberofMatchesRefereedinGroupStage": row["NumberofMatchesRefereedinGroupStage"],
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"NumberofMatchesRefereedinKnockoutStage": row["NumberofMatchesRefereedinKnockoutStage"],
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"AssistantRefereeWebName": row["AssistantRefereeWebName"],
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"Humidity": row["Humidity"],
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"Temperature": row["Temperature"],
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"WindSpeed": row["WindSpeed"],
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"MatchEvent": row["MatchEvent"],
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"TeamLineUps": row["TeamLineUps"],
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"TeamStats": row["TeamStats"],
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"PlayerStats": row["PlayerStats"],
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"PlayerPreMatchInfo": row["PlayerPreMatchInfo"],
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}
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#csv.field_size_limit(sys.maxsize)
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def _generate_examples(self, filepath):
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table = pq.read_table(filepath)
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for batch in table.to_batches():
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for row in batch.to_pydict():
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yield row
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#table = pq.read_table(filepath)
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#df = table.to_pandas()
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#df = pd.read_parquet(filepath)
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#'row' is a Pandas Series object representing the row data
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#Directly yield the id and row.to_dict() if the DataFrame structure matches the desired output
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#yield id, row.to_dict()
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#with open(filepath, encoding="utf-8") as f:
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#reader = pd.read_parquet(f)
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#for id, row in enumerate(reader):
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#match_event_str = row["MatchEvent"]
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#match_event_replaced = match_event_str.replace("'", '"')
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#pre_match_replaced = pre_match_replaced.replace(": nan", ": null")
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#pre_match_info = yaml.safe_load(pre_match_str)
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#yield id, {
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#"HomeTeamName": row["HomeTeamName"],
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#"AwayTeamName": row["AwayTeamName"],
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#"DateandTimeCET": row["DateandTimeCET"],
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#"MatchID": row["MatchID"],
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#"RoundName": row["RoundName"],
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#"Stage": row["Stage"],
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#"MatchDay": row["MatchDay"],
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#"Session": row["Session"],
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#"MatchMinute": row["MatchMinute"],
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#"InjuryTime": row["InjuryTime"],
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#"NumberOfPhases": row["NumberOfPhases"],
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#"Phase": row["Phase"],
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#"ScoreHome": row["ScoreHome"],
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#"ScoreAway": row["ScoreAway"],
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#"MatchStatus": row["MatchStatus"],
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#"StadiumID": row["StadiumID"],
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#"RefereeWebName": row["RefereeWebName"],
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#"NumberofMatchesRefereedPostMatch": row["NumberofMatchesRefereedPostMatch"],
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#"TotalNumberofMatchesRefereed": row["TotalNumberofMatchesRefereed"],
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#"NumberofMatchesRefereedinGroupStage": row["NumberofMatchesRefereedinGroupStage"],
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#"NumberofMatchesRefereedinKnockoutStage": row["NumberofMatchesRefereedinKnockoutStage"],
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#"AssistantRefereeWebName": row["AssistantRefereeWebName"],
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#"Humidity": row["Humidity"],
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#"Temperature": row["Temperature"],
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#"WindSpeed": row["WindSpeed"],
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#"MatchEvent": row["MatchEvent"],
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#"TeamLineUps": row["TeamLineUps"],
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#"TeamStats": row["TeamStats"],
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#"PlayerStats": row["PlayerStats"],
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#"PlayerPreMatchInfo": row["PlayerPreMatchInfo"],
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#}
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