add files

.gitattributes

@@ -39,3 +39,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.mp3 filter=lfs diff=lfs merge=lfs -text
 *.ogg filter=lfs diff=lfs merge=lfs -text
 *.wav filter=lfs diff=lfs merge=lfs -text
+*.csv filter=lfs diff=lfs merge=lfs -text

dataset_infos.json

@@ -0,0 +1 @@
+{"default": {"description": "This dataset is built as a playground for beginner to make a use case for creating sentiment analysis model.\n", "citation": "", "homepage": "https://github.com/jakartaresearch", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "indonews", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 7800430, "num_examples": 6127, "dataset_name": "indonews"}, "validation": {"name": "validation", "num_bytes": 3334930, "num_examples": 2627, "dataset_name": "indonews"}}, "download_checksums": {"https://media.githubusercontent.com/media/jakartaresearch/hf-datasets/main/indonews/indonews/train.csv": {"num_bytes": 7797798, "checksum": "73338405e1e5ba0138b530179ed9744e877a0a5b72231f227c8d9fa5d8e94a5b"}, "https://media.githubusercontent.com/media/jakartaresearch/hf-datasets/main/indonews/indonews/validation.csv": {"num_bytes": 3333629, "checksum": "f9d8109ab57a51a68f598f58f4294e8785aca71a6b3f2de619040f01a6494c60"}}, "download_size": 11131427, "post_processing_size": null, "dataset_size": 11135360, "size_in_bytes": 22266787}}

indonews.py

@@ -0,0 +1,75 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# TODO: Address all TODOs and remove all explanatory comments
+"""Google Play Review: An Indonesian App Sentiment Analysis."""
+
+
+import csv
+import json
+import os
+
+import datasets
+
+_DESCRIPTION = """\
+This dataset is built as a playground for beginner to make a use case for creating sentiment analysis model.
+"""
+
+_HOMEPAGE = "https://github.com/jakartaresearch"
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_TRAIN_URL = "https://media.githubusercontent.com/media/jakartaresearch/hf-datasets/main/indonews/indonews/train.csv"
+_VAL_URL = "https://media.githubusercontent.com/media/jakartaresearch/hf-datasets/main/indonews/indonews/validation.csv"
+
+
+# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
+class Indonews(datasets.GeneratorBasedBuilder):
+    """Indonews: Multiclass News Categorization scrapped popular news portals in Indonesia.."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        
+        features = datasets.Features(
+            {
+                "text": datasets.Value("string"),
+                "label": datasets.Value("string"),
+            }
+        )
+        
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE
+        )
+
+    def _split_generators(self, dl_manager):
+
+        train_path = dl_manager.download_and_extract(_TRAIN_URL)
+        val_path = dl_manager.download_and_extract(_VAL_URL)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": val_path})
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath):
+        """Generate examples."""
+        with open(filepath, encoding="utf-8") as csv_file:
+            csv_reader = csv.reader(csv_file, delimiter=",")
+            next(csv_reader)
+            for id_, row in enumerate(csv_reader):
+                text, label = row
+                yield id_, {"text": text, "label": label}