Convert dataset to Parquet (#2)

- Convert dataset to Parquet (b759b14f8e3f64ea0471b38fad3943f12c59b27c)
- Delete loading script (97632ecc766c612b0e4ce16c191527a55962ea02)
- Delete legacy dataset_infos.json (2a5e63e8936fd767d3d9a6d30599868cad6bbc11)

README.md

@@ -19,6 +19,7 @@ task_ids:
 - sentiment-classification
 pretty_name: Arabic Jordanian General Tweets
 dataset_info:
+  config_name: plain_text
   features:
   - name: text
     dtype: string
@@ -28,13 +29,18 @@ dataset_info:
         names:
           '0': Negative
           '1': Positive
-  config_name: plain_text
   splits:
   - name: train
-    num_bytes: 175424
+    num_bytes: 175420
     num_examples: 1800
-  download_size: 107395
-  dataset_size: 175424
+  download_size: 91857
+  dataset_size: 175420
+configs:
+- config_name: plain_text
+  data_files:
+  - split: train
+    path: plain_text/train-*
+  default: true
 ---
 
 # Dataset Card for Arabic Jordanian General Tweets

ajgt_twitter_ar.py

@@ -1,105 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
-#
-# 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.
-
-# Lint as: python3
-"""Arabic Jordanian General Tweets."""
-
-
-import os
-
-import openpyxl  # noqa: requires this pandas optional dependency for reading xlsx files
-import pandas as pd
-
-import datasets
-from datasets.tasks import TextClassification
-
-
-_DESCRIPTION = """\
-Arabic Jordanian General Tweets (AJGT) Corpus consisted of 1,800 tweets \
-annotated as positive and negative. Modern Standard Arabic (MSA) or Jordanian dialect.
-"""
-
-_CITATION = """\
-@inproceedings{alomari2017arabic,
-  title={Arabic tweets sentimental analysis using machine learning},
-  author={Alomari, Khaled Mohammad and ElSherif, Hatem M and Shaalan, Khaled},
-  booktitle={International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems},
-  pages={602--610},
-  year={2017},
-  organization={Springer}
-}
-"""
-
-_URL = "https://raw.githubusercontent.com/komari6/Arabic-twitter-corpus-AJGT/master/"
-
-
-class AjgtConfig(datasets.BuilderConfig):
-    """BuilderConfig for Ajgt."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for Ajgt.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(AjgtConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-
-
-class AjgtTwitterAr(datasets.GeneratorBasedBuilder):
-    """Ajgt dataset."""
-
-    BUILDER_CONFIGS = [
-        AjgtConfig(
-            name="plain_text",
-            description="Plain text",
-        )
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(
-                        names=[
-                            "Negative",
-                            "Positive",
-                        ]
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://github.com/komari6/Arabic-twitter-corpus-AJGT",
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="text", label_column="label")],
-        )
-
-    def _split_generators(self, dl_manager):
-        urls_to_download = {
-            "train": os.path.join(_URL, "AJGT.xlsx"),
-        }
-        downloaded_files = dl_manager.download(urls_to_download)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Generate examples."""
-        with open(filepath, "rb") as f:
-            df = pd.read_excel(f, engine="openpyxl")
-            for id_, record in df.iterrows():
-                tweet, sentiment = record["Feed"], record["Sentiment"]
-                yield str(id_), {"text": tweet, "label": sentiment}

dataset_infos.json

@@ -1 +0,0 @@
-{"plain_text": {"description": "Arabic Jordanian General Tweets (AJGT) Corpus consisted of 1,800 tweets annotated as positive and negative. Modern Standard Arabic (MSA) or Jordanian dialect.\n", "citation": "@inproceedings{alomari2017arabic,\n  title={Arabic tweets sentimental analysis using machine learning},\n  author={Alomari, Khaled Mohammad and ElSherif, Hatem M and Shaalan, Khaled},\n  booktitle={International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems},\n  pages={602--610},\n  year={2017},\n  organization={Springer}\n}\n", "homepage": "https://github.com/komari6/Arabic-twitter-corpus-AJGT", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["Negative", "Positive"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "label", "labels": ["Negative", "Positive"]}], "builder_name": "ajgt_twitter_ar", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 175424, "num_examples": 1800, "dataset_name": "ajgt_twitter_ar"}}, "download_checksums": {"https://raw.githubusercontent.com/komari6/Arabic-twitter-corpus-AJGT/master/AJGT.xlsx": {"num_bytes": 107395, "checksum": "966c52213872b6b8a3ced5fb7c60aee2abf47ca673c7d2c2eeb064a60bc9ed51"}}, "download_size": 107395, "post_processing_size": null, "dataset_size": 175424, "size_in_bytes": 282819}}

plain_text/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d6f35180ab9678918a07d4faf67c4b2d6c2ae29e7b2c467a990b5ec395deee9e
+size 91857