Add dataset script

dataset_script.py

@@ -0,0 +1,84 @@
+import os
+import pandas as pd
+import datasets
+
+# Define the dataset
+class MyCsvDataset(datasets.GeneratorBasedBuilder):
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features({
+                "TrackName": datasets.Value("string"),
+                "TrackID": datasets.Value("int32"),
+                "SampleURL": datasets.Value("string"),
+                "ReleaseYear": datasets.Value("int32"),
+                "Genres": datasets.Value("string"),
+                "danceability": datasets.Value("float32"),
+                "energy": datasets.Value("float32"),
+                "loudness": datasets.Value("float32"),
+                "speechiness": datasets.Value("float32"),
+                "acousticness": datasets.Value("float32"),
+                "instrumentalness": datasets.Value("float32"),
+                "liveness": datasets.Value("float32"),
+                "valence": datasets.Value("float32"),
+                "tempo": datasets.Value("float32"),
+                "key": datasets.Value("int32"),
+                "mode": datasets.Value("int32"),
+                "duration_ms": datasets.Value("int32"),
+                "Popularity": datasets.Value("int32"),
+                "pNum": datasets.Value("int32"),
+                "playlistID": datasets.Value("string"),
+                "label": datasets.Value("string"),
+                "userCat": datasets.Value("string"),
+                "demoCat": datasets.Value("string"),
+                "length": datasets.Value("int32"),
+                "playlistTitle": datasets.Value("string"),
+                "nFoll": datasets.Value("int32"),
+                "nTracks": datasets.Value("int32"),
+            })
+        )
+
+    def _split_generators(self, dl_manager):
+        # Define the dataset splits
+        data_dir = dl_manager.download_and_extract("path_to_your_data")
+        csv_file = os.path.join(data_dir, "your_dataset.csv")
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"csv_file": csv_file},
+            ),
+        ]
+
+    def _generate_examples(self, csv_file):
+        # Yield examples from the CSV file
+        df = pd.read_csv(csv_file)
+        for idx, row in df.iterrows():
+            yield idx, {
+                "TrackName": row["TrackName"],
+                "TrackID": row["TrackID"],
+                "SampleURL": row["SampleURL"],
+                "ReleaseYear": row["ReleaseYear"],
+                "Genres": row["Genres"],
+                "danceability": row["danceability"],
+                "energy": row["energy"],
+                "loudness": row["loudness"],
+                "speechiness": row["speechiness"],
+                "acousticness": row["acousticness"],
+                "instrumentalness": row["instrumentalness"],
+                "liveness": row["liveness"],
+                "valence": row["valence"],
+                "tempo": row["tempo"],
+                "key": row["key"],
+                "mode": row["mode"],
+                "duration_ms": row["duration_ms"],
+                "Popularity": row["Popularity"],
+                "pNum": row["pNum"],
+                "playlistID": row["playlistID"],
+                "label": row["label"],
+                "userCat": row["userCat"],
+                "demoCat": row["demoCat"],
+                "length": row["length"],
+                "playlistTitle": row["playlistTitle"],
+                "nFoll": row["nFoll"],
+                "nTracks": row["nTracks"],
+            }