Update Integration

Integration

@@ -2,52 +2,132 @@ from datasets import DatasetBuilder, DatasetInfo, Features, Value, SplitGenerato
 import pandas as pd
 
 class Euro2020Dataset(DatasetBuilder):
-    VERSION = "1.0.0"  # Change as needed
-    BUILDER_CONFIGS = ["euro2020"]  # Not strictly necessary but useful for multiple datasets
+    VERSION = "1.0.0" 
 
     def _info(self):
         return DatasetInfo(
             description="Your dataset description here.",
             features=Features({
-                "PlayerID": Value("int32"),
-                "PlayerName": Value("string"),
-                "PlayerSurname": Value("string"),
-                "IsGoalkeeper": Value("bool"),
-                "PlayedTime": Value("int32"),
-                "StatsID": Value("int32"),
-                "StatsName": Value("string"),
-                "Value": Value("string"),  # Adjust according to actual content type
-                "Rank": Value("int32"),
-                # Add or remove columns as needed
+                "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",
-            citation="Optional citation",
+            license= "",
+            citation="Optional citation"
         )
 
     def _split_generators(self, dl_manager):
-        # Here you define how the data should be split (train, test, validation, etc.)
-        # Since you have a single CSV file, let's assume a single 'train' split for simplicity
+        # 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 wil just use a single 'train' split and no need for test / validation.
         return [
             SplitGenerator(
                 name="train",
-                gen_kwargs={"filepath": "path/to/your/euro2020.csv"}
+                gen_kwargs={"filepath": "/Users/chuhanguo/Desktop/Winter 2024/STA 663/Euro2020.csv"}
             ),
         ]
 
-    def _generate_examples(self, filepath):
-        # Here we read the CSV file and yield examples
-        data = pd.read_csv(filepath)
-        for idx, row in data.iterrows():
-            yield idx, {
-                "PlayerID": row["PlayerID"],
-                "PlayerName": row["PlayerName"],
-                "PlayerSurname": row["PlayerSurname"],
-                "IsGoalkeeper": row["IsGoalkeeper"],
-                "PlayedTime": row["PlayedTime"],
-                "StatsID": row["StatsID"],
-                "StatsName": row["StatsName"],
-                "Value": row["Value"],
-                "Rank": row["Rank"],
+    #def _generate_examples(self, filepath):
+        #Here we read the CSV file and yield examples
+        #data = pd.read_csv(filepath)
+        #for idx, row in data.iterrows():
+            #yield idx, {
+                #"PlayerID": row["PlayerID"],
+                #"PlayerName": row["PlayerName"],
+                #"PlayerSurname": row["PlayerSurname"],
+                #"IsGoalkeeper": row["IsGoalkeeper"],
+                #"PlayedTime": row["PlayedTime"],
+                #"StatsID": row["StatsID"],
+                #"StatsName": row["StatsName"],
+                #"Value": row["Value"],
+                #"Rank": row["Rank"],
                 # Make sure to include all fields defined in _info
-            }
+            #}