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README.md

@@ -5,7 +5,7 @@ tags:
 - heart failure
 - tabular_classification
 - binary_classification
-pretty_name: Student Performance
+pretty_name: Heart failure
 size_categories:
 - 100<n<1K
 task_categories:  # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
@@ -14,4 +14,26 @@ configs:
 - death
 ---
 # Heart failure
-The [Heart failure dataset](https://www.kaggle.com/datasets/andrewmvd/heart-failure-clinical-data) is cool.
+The [Heart failure dataset](https://www.kaggle.com/datasets/andrewmvd/heart-failure-clinical-data) from Kaggle.
+
+
+# Configurations and tasks
+The dataset has the following configurations:
+- `death`, for binary classification of the patient death.
+
+
+# Features
+|**Feature**                                        |**Type**   |
+|---------------------------------------------------|-----------|
+|`age`                                               |`int8`     |
+|`has_anaemia`                                       |`int8`     |
+|`creatinine_phosphokinase_concentration_in_blood`   |`float64`  |
+|`has_diabetes`                                      |`int8`     |
+|`heart_ejection_fraction`                           |`float64`  |
+|`has_high_blood_pressure`                           |`int8`     |
+|`platelets_concentration_in_blood`                  |`float64`  |
+|`serum_creatinine_concentration_in_blood`           |`float64`  |
+|`serum_sodium_concentration_in_blood`               |`float64`  |
+|`sex`                                               |`int8`     |
+|`is_smoker`                                         |`int8`     |
+|`days_in_study`                                     |`int64`    |

heart_failure.py

@@ -1,7 +1,6 @@
 """Heart Failure Dataset"""
 
 from typing import List
-from functools import partial
 
 import datasets
 
@@ -79,27 +78,25 @@ class HeartFailure(datasets.GeneratorBasedBuilder):
         return info
     
     def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        print("downloading...")
         downloads = dl_manager.download_and_extract(urls_per_split)
-        print("downloaded!")
 
         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)
+        if config == "death":
+            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
+                yield row_id, data_row
+        else:
+            raise ValueError(f"Unknown config: {config}") 
 
     def preprocess(self, data: pandas.DataFrame, config: str = "death") -> pandas.DataFrame:
         data.columns = _BASE_FEATURE_NAMES
-        
-        if config == "death":
-            return data
-        else:
-            raise ValueError(f"Unknown config: {config}")              
+
+        return data