Update heart_failure.py

heart_failure.py

@@ -36,16 +36,16 @@ urls_per_split = {
 features_types_per_config = {
     "death": {
         "age": datasets.Value("int8"),
-        "has_anaemia": datasets.Value("int8"),
+        "has_anaemia": datasets.Value("bool"),
         "creatinine_phosphokinase_concentration_in_blood": datasets.Value("float64"),
-        "has_diabetes": datasets.Value("int8"),
+        "has_diabetes": datasets.Value("bool"),
         "heart_ejection_fraction": datasets.Value("float64"),
-        "has_high_blood_pressure": datasets.Value("int8"),
+        "has_high_blood_pressure": datasets.Value("bool"),
         "platelets_concentration_in_blood": datasets.Value("float64"),
         "serum_creatinine_concentration_in_blood": datasets.Value("float64"),
         "serum_sodium_concentration_in_blood": datasets.Value("float64"),
-        "sex": datasets.Value("int8"),
-        "is_smoker": datasets.Value("int8"),
+        "is_male": datasets.Value("bool"),
+        "is_smoker": datasets.Value("bool"),
         "days_in_study": datasets.Value("int64"),
         "is_dead": datasets.ClassLabel(num_classes=2, names=("no", "yes"))
     }
@@ -85,18 +85,30 @@ class HeartFailure(datasets.GeneratorBasedBuilder):
         ]
     
     def _generate_examples(self, filepath: str):
-        if self.config.name == "death":
-            data = pandas.read_csv(filepath)
-            data = self.preprocess(data, config=self.config.name)
+        data = pandas.read_csv(filepath)
+        data = self.preprocess(data, config=self.config.name)
 
-            for row_id, row in data.iterrows():
-                data_row = dict(row)
+        for row_id, row in data.iterrows():
+            data_row = dict(row)
 
-                yield row_id, data_row
-        else:
-            raise ValueError(f"Unknown config: {config}") 
+            yield row_id, data_row
 
     def preprocess(self, data: pandas.DataFrame, config: str = "death") -> pandas.DataFrame:
         data.columns = _BASE_FEATURE_NAMES
+        data = data.astype({"has_anaemia": "bool", "has_diabetes": "bool", "has_high_blood_pressure": "bool", "is_male": "bool",
+                            "is_smoker": "bool"})
+        "age": datasets.Value("int8"),
+        "has_anaemia": datasets.Value("bool"),
+        "creatinine_phosphokinase_concentration_in_blood": datasets.Value("float64"),
+        "has_diabetes": datasets.Value("bool"),
+        "heart_ejection_fraction": datasets.Value("float64"),
+        "has_high_blood_pressure": datasets.Value("bool"),
+        "platelets_concentration_in_blood": datasets.Value("float64"),
+        "serum_creatinine_concentration_in_blood": datasets.Value("float64"),
+        "serum_sodium_concentration_in_blood": datasets.Value("float64"),
+        "is_male": datasets.Value("bool"),
+        "is_smoker": datasets.Value("bool"),
+        "days_in_study": datasets.Value("int64"),
+        "is_dead": datasets.ClassLabel(num_classes=2, names=("no", "yes"))
 
         return data