Update parquet files

README.md

@@ -1,21 +0,0 @@
----
-language:
-- en
-tags:
-- golf
-- tabular_classification
-- binary_classification
-pretty_name: Golf
-task_categories:  # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
-- tabular-classification
-configs:
-- golf
----
-# Golf
-The Golf dataset.
-Is it a good day to play golf?
-
-# Configurations and tasks
-| **Configuration**     | **Task**                  |
-|-----------------------|---------------------------|
-| golf                  | Binary classification.|

golf.data

@@ -1,15 +0,0 @@
-outlook,temperature,humidity,windy,goodPlaying,toPlay
-sunny,85,85,false,1,Don't Play
-sunny,80,90,true,1,Don't Play
-overcast,83,78,false,1.5,Play
-rain,70,96,false,0.8,Play
-rain,68,80,false,2,Play
-rain,65,70,true,1,Don't Play
-overcast,64,65,true,2.5,Play
-sunny,72,95,false,1,Don't Play
-sunny,69,70,false,1,Play
-rain,75,80,false,1.5,Play
-sunny,75,70,true,3,Play
-overcast,72,90,true,1.5,Play
-overcast,81,75,false,1,Play
-rain,71,80,true,1,Don't Play

golf.py

@@ -1,90 +0,0 @@
-"""Golf Dataset"""
-
-from typing import List
-from functools import partial
-
-import datasets
-
-import pandas
-
-
-VERSION = datasets.Version("1.0.0")
-
-_ENCODING_DICS = {
-	"toPlay": {
-		"Don't Play": 0,
-		"Play": 1
-	}
-}
-
-DESCRIPTION = "Golf dataset."
-_HOMEPAGE = ""
-_URLS = ("")
-_CITATION = """"""
-
-# Dataset info
-urls_per_split = {
-	"train": "https://huggingface.co/datasets/mstz/golf/resolve/main/golf.data"
-}
-features_types_per_config = {
-	"golf": {
-		"outlook": datasets.Value("string"),
-		"temperature": datasets.Value("int8"),
-		"humidity": datasets.Value("int8"),
-		"windy": datasets.Value("bool"),
-		"goodPlaying": datasets.Value("float64"),
-		"toPlay": datasets.ClassLabel(num_classes=2, names=("no", "yes"))
-	}
-}
-features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
-
-
-class GolfConfig(datasets.BuilderConfig):
-	def __init__(self, **kwargs):
-		super(GolfConfig, self).__init__(version=VERSION, **kwargs)
-		self.features = features_per_config[kwargs["name"]]
-
-
-class Golf(datasets.GeneratorBasedBuilder):
-	# dataset versions
-	DEFAULT_CONFIG = "golf"
-	BUILDER_CONFIGS = [
-		GolfConfig(name="golf", description="Golf for binary classification.")		
-	]
-
-
-	def _info(self):
-		info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
-									features=features_per_config[self.config.name])
-
-		return info
-	
-	def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-		downloads = dl_manager.download_and_extract(urls_per_split)
-
-		return [
-			datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]}),
-		]
-	
-	def _generate_examples(self, filepath: str):
-		data = pandas.read_csv(filepath)
-		data = self.preprocess(data)
-
-		for row_id, row in data.iterrows():
-			data_row = dict(row)
-
-			yield row_id, data_row
-
-	def preprocess(self, data: pandas.DataFrame) -> pandas.DataFrame:
-		print(data.dtypes)	
-		print(data.windy.unique())	
-		for feature in _ENCODING_DICS:
-			encoding_function = partial(self.encode, feature)
-			data.loc[:, feature] = data[feature].apply(encoding_function)
-				
-		return data[list(features_types_per_config[self.config.name].keys())]
-
-	def encode(self, feature, value):
-		if feature in _ENCODING_DICS:
-			return _ENCODING_DICS[feature][value]
-		raise ValueError(f"Unknown feature: {feature}")

golf/golf-train.parquet

@@ -0,0 +1,3 @@
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+oid sha256:c47e7b6a1788f7216d1e7d02be242236ed733bb489d1fadd34177d6976e0d5a3
+size 3268