Upload heart.py

heart.py

@@ -112,6 +112,14 @@ features_types_per_config = {
 }
 features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
 
+_ENCODING_DICS = {
+    "type_of_chest_pain": {
+        1: "typical angina"
+        2: "atypical angina"
+        3: "non-anginal pain"
+        4: "asymptomatic"
+    }
+}
 
 class HeartConfig(datasets.BuilderConfig):
     def __init__(self, **kwargs):
@@ -151,16 +159,27 @@ class Heart(datasets.GeneratorBasedBuilder):
         data = pandas.read_csv(filepath, header=None)
         data.columns = _BASE_FEATURE_NAMES
 
-        data = data.astype({"is_male": bool, "has_exercise_induced_angina": bool})
+        for feature in _ENCODING_DICS:
+            encoding_function = partial(self.encode, feature)
+            data.loc[:, feature] = data[feature].apply(encoding_function)
 
+        data = data.astype({"is_male": bool, "has_exercise_induced_angina": bool})
+        data.age.applymap(int)
         data = data[data.thal != "?"]
         data = data[data.number_of_major_vessels_colored_by_flourosopy != "?"]
         data = data.infer_objects()
 
         print(data.head())
         print(data.dtypes)
+        print(data.number_of_major_vessels_colored_by_flourosopy.unique())
+        print(data.thal.unique())
 
         for row_id, row in data.iterrows():
             data_row = dict(row)
 
             yield row_id, data_row
+
+    def encode(self, feature, value):
+        if feature in _ENCODING_DICS:
+            return _ENCODING_DICS[feature][value]
+        raise ValueError(f"Unknown feature: {feature}")