Update bank.py

bank.py

@@ -90,10 +90,10 @@ features_types_per_config = {
         "job": datasets.Value("string"),
         "marital_status": datasets.Value("string"),
         "education_level": datasets.Value("int8"),
-        "has_defaulted": datasets.Value("int8"),
+        "has_defaulted": datasets.Value("bool"),
         "account_balance": datasets.Value("int64"),
-        "has_housing_loan": datasets.Value("int8"),
-        "has_personal_loan": datasets.Value("int8"),
+        "has_housing_loan": datasets.Value("bool"),
+        "has_personal_loan": datasets.Value("bool"),
         "month_of_last_contact": datasets.Value("string"),
         "number_of_calls_in_ad_campaign": datasets.Value("string"),
         "days_since_last_contact_of_previous_campaign": datasets.Value("int16"),
@@ -123,9 +123,6 @@ class Bank(datasets.GeneratorBasedBuilder):
 
 
     def _info(self):
-        if self.config.name not in features_per_config:
-            raise ValueError(f"Unknown configuration: {self.config.name}")
-        
         info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
                                     features=features_per_config[self.config.name])
 
@@ -150,22 +147,24 @@ class Bank(datasets.GeneratorBasedBuilder):
 
             yield row_id, data_row
 
-    def preprocess(self, data: pandas.DataFrame, config: str = "subscription") -> pandas.DataFrame:
-        if config == "subscription":
-            data.drop("day", axis="columns", inplace=True)
-            data.drop("contact", axis="columns", inplace=True)
-            data.drop("duration", axis="columns", inplace=True)
-            data.drop("poutcome", axis="columns", inplace=True)
+    def preprocess(self, data: pandas.DataFrame, config: str = DEFAULT_CONFIG) -> pandas.DataFrame:
+        data.drop("day", axis="columns", inplace=True)
+        data.drop("contact", axis="columns", inplace=True)
+        data.drop("duration", axis="columns", inplace=True)
+        data.drop("poutcome", axis="columns", inplace=True)
 
-            data.columns = _BASE_FEATURE_NAMES
+        data.columns = _BASE_FEATURE_NAMES
 
-            for feature in _ENCODING_DICS:
-                encoding_function = partial(self.encode, feature)
-                data.loc[:, feature] = data[feature].apply(encoding_function)
+        for feature in _ENCODING_DICS:
+            encoding_function = partial(self.encode, feature)
+            data.loc[:, feature] = data[feature].apply(encoding_function)
+        data = data.astype({
+            "has_defaulted": "bool",
+            "has_housing_loan": "bool",
+            "has_personal_loan": "bool"
+        })
 
-            return data
-        else:
-            raise ValueError(f"Unknown config: {config}")
+        return data
        
     def encode(self, feature, value):
         if feature in _ENCODING_DICS: