UEFA_Euro_2020_Data / Integration
ForzaJuve1's picture
Update Integration
ab18d14 verified
raw
history blame
2.17 kB
from datasets import DatasetBuilder, DatasetInfo, Features, Value, SplitGenerator
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
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
}),
supervised_keys=None,
homepage="Optional dataset homepage",
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
return [
SplitGenerator(
name="train",
gen_kwargs={"filepath": "path/to/your/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"],
# Make sure to include all fields defined in _info
}