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README.md

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 ---
-license: cc-by-4.0
+language:
+- en
+tags:
+- adult
+- tabular_classification
+- binary_classification
+- multiclass_classification
+pretty_name: Adult
+size_categories:
+- 10K<n<100K
+task_categories:  # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
+- tabular-classification
+configs:
+- encoding
+- income
+- income-no race
+- race
 ---
+# Adult
+The [Adult dataset](https://archive.ics.uci.edu/ml/datasets/Adult) from the [UCI ML repository](https://archive.ics.uci.edu/ml/datasets).
+Census dataset including personal characteristic of a person, and their income threshold.
+
+# Configurations and tasks
+| **Configuration** | **Task**                  | **Description**                                               |
+|-------------------|---------------------------|---------------------------------------------------------------|
+| encoding          |                           | Encoding dictionary                                           |
+| income            | Binary classification     | Classify the person's income as over or under the threshold.  |
+| income-no race    | Binary classification     | As `income`, but the `race` feature is removed.               |
+| race              | Multiclass classification | Predict the race of the individual.                           |
+
+# Usage
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("mstz/adult", "income")["train"]
+```
+
+# Features
+|**Feature**        |**Type**   | **Description**                                           |
+|-------------------|-----------|-----------------------------------------------------------|
+|`age`              |`[int64]`  | Age of the person                                         |
+|`capital_gain`     |`[float64]`| Capital gained by the person                              |
+|`capital_loss`     |`[float64]`| Capital lost by the person                                |
+|`education`        |`[int8]`   | Education level: the higher, the more educated the person |
+|`final_weight`     |`[int64]`  |                                                           |
+|`hours_per_week`   |`[int64]`  | Hours worked per week                                     |
+|`marital_status`   |`[string]` | Marital status of the person                              |
+|`native_country`   |`[string]` | Native country of the person                              |
+|`occupation`       |`[string]` | Job of the person                                         |
+|`race`             |`[string]` | Race of the person                                        |
+|`relationship`     |`[string]` |                                                           |
+|`sex`              |`[int8]`   | Sex of the person                                         |
+|`workclass`        |`[string]` | Type of job of the person                                 |
+|`over_threshold`   |`int8`     |`1` for income `>= 50k$`, `0` otherwise                    |

mushroom.py

@@ -0,0 +1,329 @@
+"""Mushroom"""
+
+from typing import List
+from functools import partial
+
+import datasets
+
+import pandas, numpy
+
+
+VERSION = datasets.Version("1.0.0")
+_ORIGINAL_FEATURE_NAMES = [
+    "is_poisonous",
+    "cap_shape",
+    "cap_surface",
+    "cap_color",
+    "has_bruises",
+    "odor",
+    "gill_attachment",
+    "gill_spacing",
+    "gill_size",
+    "gill_color",
+    "stalk_shape",
+    "stalk_root",
+    "stalk_surface_above_ring",
+    "stalk_surface_belows_ring",
+    "stalk_color_above_ring",
+    "stalk_color_belows_ring",
+    "veil_type",
+    "veil_color",
+    "number_of_rings",
+    "ring_type",
+    "spore_print_color",
+    "population",
+    "habitat",
+    "is_poisonous"
+]
+_BASE_FEATURE_NAMES = [
+    "cap_shape",
+    "cap_surface",
+    "cap_color",
+    "has_bruises",
+    "odor",
+    "gill_attachment",
+    "gill_spacing",
+    "gill_size",
+    "gill_color",
+    "stalk_shape",
+    "stalk_surface_above_ring",
+    "stalk_surface_belows_ring",
+    "stalk_color_above_ring",
+    "stalk_color_belows_ring",
+    "veil_type",
+    "veil_color",
+    "number_of_rings",
+    "ring_type",
+    "spore_print_color",
+    "population",
+    "habitat"
+]
+
+_ENCODING_DICS = {
+    "is_poisonous": {
+        "p": 1,
+        "e": 0
+    },
+    "cap_shape":  {
+        "b": "bell",
+        "c": "conical",
+        "x": "convex",
+        "f": "flat",
+        "k": "knobbed",
+        "s": "sunken",
+    },
+    "cap_surface": {
+        "f": "fibrous",
+        "g": "grooves",
+        "y": "scaly",
+        "s": "smooth"
+    },
+    "cap_color": {
+        "n": "brown",
+        "b": "buff",
+        "c": "cinnamon",
+        "g": "gray",
+        "r": "green",
+        "p": "pink",
+        "u": "purple",
+        "e": "red",
+        "w": "white",
+        "y": "yellow"
+    },
+    "has_bruises": {
+        "f": False,
+        "t": True
+    },
+    "odor": {
+        "a": "almond",
+        "l": "anise",
+        "c": "creosote",
+        "y": "fishy",
+        "f": "foul",
+        "m": "musty",
+        "n": "none",
+        "p": "pungent",
+        "s": "spicy"
+    },
+    "gill_attachment": {
+        "a": "attached",
+        "d": "descending",
+        "f": "free",
+        "n": "notched",
+    },
+    "gill_spacing": {
+        "c": "close",
+        "w": "crowded",
+        "d": "distant",
+    },
+    "gill_size": {
+        "b": "broad",
+        "n": "narrow"
+    },
+    "gill_color": {
+        "k": "black",
+        "n": "brown",
+        "b": "buff",
+        "h": "chocolate",
+        "g": "gray",
+        "r": "green",
+        "o": "orange",
+        "p": "pink",
+        "u": "purple",
+        "e": "red",
+        "w": "white",
+        "y": "yellow",
+    },
+    "stalk_shape": {
+        "e": "enlarging",
+        "t": "tapering",
+    },
+    "stalk_surface_above_ring": {
+        "f": "fibrous",
+        "y": "scaly",
+        "k": "silky",
+        "s": "smooth",
+    },
+    "stalk_surface_above_ring": {
+        "f": "fibrous",
+        "y": "scaly",
+        "k": "silky",
+        "s": "smooth",
+    },
+    "stalk_color_above_ring": {
+        "n": "brown",
+        "b": "buff",
+        "c": "cinnamon",
+        "g": "gray",
+        "o": "orange",
+        "p": "pink",
+        "e": "red",
+        "w": "white",
+        "y": "yellow",
+    },
+    "stalk_color_below_ring": {
+        "n": "brown",
+        "b": "buff",
+        "c": "cinnamon",
+        "g": "gray",
+        "o": "orange",
+        "p": "pink",
+        "e": "red",
+        "w": "white",
+        "y": "yellow",
+    },
+    "veil_type": {
+        "p": "partial",
+        "u": "universal",
+    },
+    "veil_color": {
+        "n": "brown",
+        "o": "orange",
+        "w": "white",
+        "y": "yellow",
+    },
+    "ring_number": {
+        "n": 0,
+        "o": 1,
+        "t": 2,
+    },
+    "ring_type": {
+        "c": "cobwebby",
+        "e": "evanescent",
+        "f": "flaring",
+        "l": "large",
+        "n": "none",
+        "p": "pendant",
+        "s": "sheathing",
+        "z": "zone",
+    },
+    "spore_print_color": {
+        "k": "black",
+        "n": "brown",
+        "b": "buff",
+        "h": "chocolate",
+        "r": "green",
+        "o": "orange",
+        "u": "purple",
+        "w": "white",
+        "y": "yellow",
+    },
+    "population": {
+        "a": "abundant",
+        "c": "clustered",
+        "n": "numerous",
+        "s": "scattered",
+        "v": "several",
+        "y": "solitary",
+    },
+    "habitat": {
+        "g": "grasses",
+        "l": "leaves",
+        "m": "meadows",
+        "p": "paths",
+        "u": "urban",
+        "w": "waste",
+        "d": "woods",
+    }
+}
+
+DESCRIPTION = "Mushroom dataset from the UCI ML repository."
+_HOMEPAGE = "https://archive.ics.uci.edu/ml/datasets/Mushroom"
+_URLS = ("https://huggingface.co/datasets/mstz/mushroom/raw/mushroom.csv")
+_CITATION = """
+@misc{misc_mushroom_73,
+  title        = {{Mushroom}},
+  year         = {1987},
+  howpublished = {UCI Machine Learning Repository},
+  note         = {{DOI}: \\url{10.24432/C5959T}}
+}"""
+
+# Dataset info
+urls_per_split = {
+    "train": "https://huggingface.co/datasets/mstz/mushroom/raw/main/agaricus-lepiota.data"
+}
+features_types_per_config = {
+    "mushroom": {
+        "cap_shape",
+        "cap_surface",
+        "cap_color",
+        "has_bruises",
+        "odor",
+        "gill_attachment",
+        "gill_spacing",
+        "gill_size",
+        "gill_color",
+        "stalk_shape",
+        "stalk_root",
+        "stalk_surface_above_ring",
+        "stalk_surface_belows_ring",
+        "stalk_color_above_ring",
+        "stalk_color_belows_ring",
+        "veil_type",
+        "veil_color",
+        "number_of_rings",
+        "ring_type",
+        "spore_print_color",
+        "population",
+        "habitat",
+        "is_poisonous": 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 MushroomConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(MushroomConfig, self).__init__(version=VERSION, **kwargs)
+        self.features = features_per_config[kwargs["name"]]
+
+
+class Mushroom(datasets.GeneratorBasedBuilder):
+    # dataset versions
+    DEFAULT_CONFIG = "mushroom"
+    BUILDER_CONFIGS = [
+        MushroomConfig(name="mushroom",
+                    description="Mushroom 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, config=self.config.name)
+
+        for row_id, row in data.iterrows():
+            data_row = dict(row)
+
+            yield row_id, data_row
+
+
+    def preprocess(self, data: pandas.DataFrame, config: str = DEFAULT_CONFIG) -> pandas.DataFrame:     
+        data.drop("stalk_root", axis="columns", inplace=True)
+        data = data[list(features_types_per_config[config].keys())]
+
+        for feature in _ENCODING_DICS:
+            encoding_function = partial(self.encode, feature)
+            data.loc[:, feature] = data[feature].apply(encoding_function)
+        data = data.infer_objects()
+ 
+        return 
+    
+    def encode(self, feature, value):
+        if feature in _ENCODING_DICS:
+            return _ENCODING_DICS[feature][value]
+        raise ValueError(f"Unknown feature: {feature}")
+    
+    def encode_race(self, race):
+        return _RACE_ENCODING[race]