Upload covertype.py

covertype.py

@@ -3,6 +3,7 @@ from typing import List
 import datasets
 
 import pandas
+import gzip
 
 
 VERSION = datasets.Version("1.0.0")
@@ -15,8 +16,63 @@ _CITATION = """"""
 
 # Dataset info
 urls_per_split = {
-    "train": "https://huggingface.co/datasets/mstz/covertype/raw/main/covtype.data"
+    "train": "https://archive.ics.uci.edu/ml/machine-learning-databases/covtype/covtype.data.gz"
 }
+_BASE_FEATURE_NAMES = [
+    "elevation",
+    "aspect",
+    "slope",
+    "horizontal_distance_to_hydrology",
+    "vertical_distance_to_hydrology",
+    "horizontal_distance_to_roadways",
+    "hillshade_9am",
+    "hillshade_noon",
+    "hillshade_3pm",
+    "horizontal_distance_to_fire_points",
+    "is_a_wilderness_area",
+    "soil_type_id_0",
+    "soil_type_id_1",
+    "soil_type_id_2",
+    "soil_type_id_3",
+    "soil_type_id_4",
+    "soil_type_id_5",
+    "soil_type_id_6",
+    "soil_type_id_7",
+    "soil_type_id_8",
+    "soil_type_id_9",
+    "soil_type_id_10",
+    "soil_type_id_11",
+    "soil_type_id_12",
+    "soil_type_id_13",
+    "soil_type_id_14",
+    "soil_type_id_15",
+    "soil_type_id_16",
+    "soil_type_id_17",
+    "soil_type_id_18",
+    "soil_type_id_19",
+    "soil_type_id_20",
+    "soil_type_id_21",
+    "soil_type_id_22",
+    "soil_type_id_23",
+    "soil_type_id_24",
+    "soil_type_id_25",
+    "soil_type_id_26",
+    "soil_type_id_27",
+    "soil_type_id_28",
+    "soil_type_id_29",
+    "soil_type_id_30",
+    "soil_type_id_31",
+    "soil_type_id_32",
+    "soil_type_id_33",
+    "soil_type_id_34",
+    "soil_type_id_35",
+    "soil_type_id_36",
+    "soil_type_id_37",
+    "soil_type_id_38",
+    "soil_type_id_39",
+    "soil_type",
+    "cover_type"
+]
 features_types_per_config = {
     "covertype": {
         "elevation": datasets.Value("float32"),
@@ -110,7 +166,8 @@ class Covertype(datasets.GeneratorBasedBuilder):
         ]
     
     def _generate_examples(self, filepath: str):
-            data = pandas.read_csv(filepath)
+            with gzip.open(filepath) as log:
+                data = pandas.read_csv(log, header=_BASE_FEATURE_NAMES)
             data = self.preprocess(data, config=self.config.name)
 
             for row_id, row in data.iterrows():
@@ -119,7 +176,6 @@ class Covertype(datasets.GeneratorBasedBuilder):
                 yield row_id, data_row
 
     def preprocess(self, data: pandas.DataFrame, config: str = DEFAULT_CONFIG) -> pandas.DataFrame:
-        print(data.columns)
-        print(data.cover_type)
         data.loc[:, "cover_type"] = data["cover_type"].apply(lambda x: x - 1)
+        
         return data