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README.md

@@ -1,3 +1,32 @@
 ---
-license: cc-by-4.0
+language:
+- en
+tags:
+- ozone
+- tabular_classification
+- binary_classification
+pretty_name: Ozone
+size_categories:
+- 1K<n<10K
+task_categories:  # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
+- tabular-classification
+configs:
+- 8hr
+- 1hr
 ---
+# Ozone
+The [Ozone dataset](https://archive.ics.uci.edu/ml/datasets/Ozone) from the [UCI ML repository](https://archive.ics.uci.edu/ml/datasets).
+
+# Configurations and tasks
+| **Configuration** | **Task**                  | **Description**         |
+|-------------------|---------------------------|-------------------------|
+| 8hr               | Binary classification     | Is there an ozone layer?|
+| 1hr               | Binary classification     | Is there an ozone layer?|
+
+
+# Usage
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("mstz/ozone", "8hr")["train"]
+```

ozone.py

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+"""Ozone: A Census Dataset"""
+
+from typing import List
+
+import datasets
+
+import pandas
+
+
+VERSION = datasets.Version("1.0.0")
+_BASE_FEATURE_NAMES = [
+    "Date",
+	"WSR0",
+	"WSR1",
+	"WSR2",
+	"WSR3",
+	"WSR4",
+	"WSR5",
+	"WSR6",
+	"WSR7",
+	"WSR8",
+	"WSR9",
+	"WSR10",
+	"WSR11",
+	"WSR12",
+	"WSR13",
+	"WSR14",
+	"WSR15",
+	"WSR16",
+	"WSR17",
+	"WSR18",
+	"WSR19",
+	"WSR20",
+	"WSR21",
+	"WSR22",
+	"WSR23",
+	"WSR_PK",
+	"WSR_AV",
+	"T0",
+	"T1",
+	"T2",
+	"T3",
+	"T4",
+	"T5",
+	"T6",
+	"T7",
+	"T8",
+	"T9",
+	"T10",
+	"T11",
+	"T12",
+	"T13",
+	"T14",
+	"T15",
+	"T16",
+	"T17",
+	"T18",
+	"T19",
+	"T20",
+	"T21",
+	"T22",
+	"T23",
+	"T_PK",
+	"T_AV",
+	"T85",
+	"RH85",
+	"U85",
+	"V85",
+	"HT85",
+	"T70",
+	"RH70",
+	"U70",
+	"V70",
+	"HT70",
+	"T50",
+	"RH50",
+	"U50",
+	"V50",
+	"HT50",
+	"KI",
+	"TT",
+	"SLP",
+	"SLP_",
+	"Precp",
+	"Class"
+]
+
+DESCRIPTION = "Ozone dataset from the UCI ML repository."
+_HOMEPAGE = "https://archive.ics.uci.edu/ml/datasets/Ozone"
+_URLS = ("https://archive.ics.uci.edu/ml/datasets/Ozone")
+_CITATION = """
+@misc{misc_ozone_level_detection_172,
+  author       = {Zhang,Kun, Fan,Wei & Yuan,XiaoJing},
+  title        = {{Ozone Level Detection}},
+  year         = {2008},
+  howpublished = {UCI Machine Learning Repository},
+  note         = {{DOI}: \\url{10.24432/C5NG6W}}
+}"""
+
+# Dataset info
+urls_per_split = {
+    "8hr": {"train": "https://huggingface.co/datasets/mstz/ozoneV2/raw/main/eighthr.data"},
+    "1hr": {"train": "https://huggingface.co/datasets/mstz/ozoneV2/raw/main/onehr.data"},
+}
+features_types_per_config = {
+    "8hr": {
+	    "WSR0": datasets.Value("float8"),
+	    "WSR1": datasets.Value("float8"),
+	    "WSR2": datasets.Value("float8"),
+	    "WSR3": datasets.Value("float8"),
+	    "WSR4": datasets.Value("float8"),
+	    "WSR5": datasets.Value("float8"),
+	    "WSR6": datasets.Value("float8"),
+	    "WSR7": datasets.Value("float8"),
+	    "WSR8": datasets.Value("float8"),
+	    "WSR9": datasets.Value("float8"),
+	    "WSR10": datasets.Value("float8"),
+	    "WSR11": datasets.Value("float8"),
+	    "WSR12": datasets.Value("float8"),
+	    "WSR13": datasets.Value("float8"),
+	    "WSR14": datasets.Value("float8"),
+	    "WSR15": datasets.Value("float8"),
+	    "WSR16": datasets.Value("float8"),
+	    "WSR17": datasets.Value("float8"),
+	    "WSR18": datasets.Value("float8"),
+	    "WSR19": datasets.Value("float8"),
+	    "WSR20": datasets.Value("float8"),
+	    "WSR21": datasets.Value("float8"),
+	    "WSR22": datasets.Value("float8"),
+	    "WSR23": datasets.Value("float8"),
+	    "WSR_PK": datasets.Value("float8"),
+	    "WSR_AV": datasets.Value("float8"),
+	    "T0": datasets.Value("float8"),
+	    "T1": datasets.Value("float8"),
+	    "T2": datasets.Value("float8"),
+	    "T3": datasets.Value("float8"),
+	    "T4": datasets.Value("float8"),
+	    "T5": datasets.Value("float8"),
+	    "T6": datasets.Value("float8"),
+	    "T7": datasets.Value("float8"),
+	    "T8": datasets.Value("float8"),
+	    "T9": datasets.Value("float8"),
+	    "T10": datasets.Value("float8"),
+	    "T11": datasets.Value("float8"),
+	    "T12": datasets.Value("float8"),
+	    "T13": datasets.Value("float8"),
+	    "T14": datasets.Value("float8"),
+	    "T15": datasets.Value("float8"),
+	    "T16": datasets.Value("float8"),
+	    "T17": datasets.Value("float8"),
+	    "T18": datasets.Value("float8"),
+	    "T19": datasets.Value("float8"),
+	    "T20": datasets.Value("float8"),
+	    "T21": datasets.Value("float8"),
+	    "T22": datasets.Value("float8"),
+	    "T23": datasets.Value("float8"),
+	    "T_PK": datasets.Value("float8"),
+	    "T_AV": datasets.Value("float8"),
+	    "T85": datasets.Value("float8"),
+	    "RH85": datasets.Value("float8"),
+	    "U85": datasets.Value("float8"),
+	    "V85": datasets.Value("float8"),
+	    "HT85": datasets.Value("float8"),
+	    "T70": datasets.Value("float8"),
+	    "RH70": datasets.Value("float8"),
+	    "U70": datasets.Value("float8"),
+	    "V70": datasets.Value("float8"),
+	    "HT70": datasets.Value("float8"),
+	    "T50": datasets.Value("float8"),
+	    "RH50": datasets.Value("float8"),
+	    "U50": datasets.Value("float8"),
+	    "V50": datasets.Value("float8"),
+	    "HT50": datasets.Value("float8"),
+	    "KI": datasets.Value("float8"),
+	    "TT": datasets.Value("float8"),
+	    "SLP": datasets.Value("float8"),
+	    "SLP_": datasets.Value("float8"),
+	    "Precp": datasets.Value("float8"),
+	    "Class": datasets.ClassLabel(num_classes=2, names=("no", "yes"))
+    },
+    "1hr": {
+	    "WSR0": datasets.Value("float8"),
+	    "WSR1": datasets.Value("float8"),
+	    "WSR2": datasets.Value("float8"),
+	    "WSR3": datasets.Value("float8"),
+	    "WSR4": datasets.Value("float8"),
+	    "WSR5": datasets.Value("float8"),
+	    "WSR6": datasets.Value("float8"),
+	    "WSR7": datasets.Value("float8"),
+	    "WSR8": datasets.Value("float8"),
+	    "WSR9": datasets.Value("float8"),
+	    "WSR10": datasets.Value("float8"),
+	    "WSR11": datasets.Value("float8"),
+	    "WSR12": datasets.Value("float8"),
+	    "WSR13": datasets.Value("float8"),
+	    "WSR14": datasets.Value("float8"),
+	    "WSR15": datasets.Value("float8"),
+	    "WSR16": datasets.Value("float8"),
+	    "WSR17": datasets.Value("float8"),
+	    "WSR18": datasets.Value("float8"),
+	    "WSR19": datasets.Value("float8"),
+	    "WSR20": datasets.Value("float8"),
+	    "WSR21": datasets.Value("float8"),
+	    "WSR22": datasets.Value("float8"),
+	    "WSR23": datasets.Value("float8"),
+	    "WSR_PK": datasets.Value("float8"),
+	    "WSR_AV": datasets.Value("float8"),
+	    "T0": datasets.Value("float8"),
+	    "T1": datasets.Value("float8"),
+	    "T2": datasets.Value("float8"),
+	    "T3": datasets.Value("float8"),
+	    "T4": datasets.Value("float8"),
+	    "T5": datasets.Value("float8"),
+	    "T6": datasets.Value("float8"),
+	    "T7": datasets.Value("float8"),
+	    "T8": datasets.Value("float8"),
+	    "T9": datasets.Value("float8"),
+	    "T10": datasets.Value("float8"),
+	    "T11": datasets.Value("float8"),
+	    "T12": datasets.Value("float8"),
+	    "T13": datasets.Value("float8"),
+	    "T14": datasets.Value("float8"),
+	    "T15": datasets.Value("float8"),
+	    "T16": datasets.Value("float8"),
+	    "T17": datasets.Value("float8"),
+	    "T18": datasets.Value("float8"),
+	    "T19": datasets.Value("float8"),
+	    "T20": datasets.Value("float8"),
+	    "T21": datasets.Value("float8"),
+	    "T22": datasets.Value("float8"),
+	    "T23": datasets.Value("float8"),
+	    "T_PK": datasets.Value("float8"),
+	    "T_AV": datasets.Value("float8"),
+	    "T85": datasets.Value("float8"),
+	    "RH85": datasets.Value("float8"),
+	    "U85": datasets.Value("float8"),
+	    "V85": datasets.Value("float8"),
+	    "HT85": datasets.Value("float8"),
+	    "T70": datasets.Value("float8"),
+	    "RH70": datasets.Value("float8"),
+	    "U70": datasets.Value("float8"),
+	    "V70": datasets.Value("float8"),
+	    "HT70": datasets.Value("float8"),
+	    "T50": datasets.Value("float8"),
+	    "RH50": datasets.Value("float8"),
+	    "U50": datasets.Value("float8"),
+	    "V50": datasets.Value("float8"),
+	    "HT50": datasets.Value("float8"),
+	    "KI": datasets.Value("float8"),
+	    "TT": datasets.Value("float8"),
+	    "SLP": datasets.Value("float8"),
+	    "SLP_": datasets.Value("float8"),
+	    "Precp": datasets.Value("float8"),
+	    "Class": 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 OzoneConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(OzoneConfig, self).__init__(version=VERSION, **kwargs)
+        self.features = features_per_config[kwargs["name"]]
+
+
+class Ozone(datasets.GeneratorBasedBuilder):
+    # dataset versions
+    DEFAULT_CONFIG = "ozone"
+    BUILDER_CONFIGS = [
+        OzoneConfig(name="8hr",
+                    description="Ozone for binary classification.")
+        OzoneConfig(name="1hr",
+                    description="Ozone 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[self.config.name]["train"]})
+        ]
+    
+    def _generate_examples(self, filepath: str):
+        data = pandas.read_csv(filepath, header=None)
+        data.columns = _BASE_FEATURE_NAMES
+        data.drop("Date", axis="columns", inplace=True)
+
+        for row_id, row in data.iterrows():
+            data_row = dict(row)
+
+            yield row_id, data_row