Upload student_performance.py

student_performance.py

@@ -63,7 +63,7 @@ features_types_per_config = {
         "ethnicity": datasets.Value("string"),
         "parental_level_of_education": datasets.Value("int8"),
         "has_standard_lunch": datasets.Value("int8"),
-        "has_completed_preparation_test": datasets.Value("string"),
+        "has_completed_preparation_test": datasets.Value("int8"),
         "reading_score": datasets.Value("int64"),
         "writing_score": datasets.Value("int64"),
         "has_passed_math_exam": datasets.ClassLabel(num_classes=2, names=("no", "yes"))
@@ -73,7 +73,7 @@ features_types_per_config = {
         "ethnicity": datasets.Value("string"),
         "parental_level_of_education": datasets.Value("int8"),
         "has_standard_lunch": datasets.Value("int8"),
-        "has_completed_preparation_test": datasets.Value("string"),
+        "has_completed_preparation_test": datasets.Value("int8"),
         "reading_score": datasets.Value("int64"),
         "math_score": datasets.Value("int64"),
         "has_passed_writing_exam": datasets.ClassLabel(num_classes=2, names=("no", "yes")),
@@ -83,7 +83,7 @@ features_types_per_config = {
         "ethnicity": datasets.Value("string"),
         "parental_level_of_education": datasets.Value("int8"),
         "has_standard_lunch": datasets.Value("int8"),
-        "has_completed_preparation_test": datasets.Value("string"),
+        "has_completed_preparation_test": datasets.Value("int8"),
         "writing_score": datasets.Value("int64"),
         "math_score": datasets.Value("int64"),
         "has_passed_reading_exam": datasets.ClassLabel(num_classes=2, names=("no", "yes")),
@@ -143,7 +143,7 @@ class StudentPerformance(datasets.GeneratorBasedBuilder):
 
             yield row_id, data_row
 
-    def preprocess(self, data: pandas.DataFrame, config: str = "cut") -> pandas.DataFrame:
+    def preprocess(self, data: pandas.DataFrame, config: str = "math") -> pandas.DataFrame:
         data.columns = _BASE_FEATURE_NAMES
         for feature in _ENCODING_DICS:
             encoding_function = partial(self.encode, feature)