Convert dataset to Parquet (#1)

- Convert dataset to Parquet (d78c52fa51a12e0bfae395c6ba7d0917b9545a73)
- Delete loading script (f3e1b9904ed692273fecbadd8889e2effabdef64)

README.md

@@ -1,5 +1,12 @@
 ---
+language:
+- en
 license: cc-by-3.0
+size_categories:
+- 1K<n<10K
+task_categories:
+- text-classification
+pretty_name: On the Books Training Set
 dataset_info:
   features:
   - name: id
@@ -26,16 +33,14 @@ dataset_info:
   - name: train
     num_bytes: 2119395
     num_examples: 1785
-  download_size: 2085196
+  download_size: 944579
   dataset_size: 2119395
-task_categories:
-- text-classification
-language:
-- en
 tags:
 - lam
 - legal
-pretty_name: On the Books Training Set
-size_categories:
-- 1K<n<10K
----
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+---

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bf1a870b62efb102b9f976adfe846937d0d66ec0a9a0316ab9e7f4c47415370e
+size 944579

on_the_books.py

@@ -1,81 +0,0 @@
-# coding=utf-8
-# Copyright 2021 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.
-"""On the Books Dataset"""
-
-import csv
-
-import datasets
-
-
-_CITATION = """TODO"""
-
-_DESCRIPTION = """\
-This file is the training set that was used to train an algorithm to identify Jim Crow laws.
-It contains laws that are labeled as "Jim Crow" (jim_crow=1) or "Not Jim Crow" (jim_crow=0).
-The source of the determination is also provided.
-
-"""
-
-_HOMEPAGE = "https://onthebooks.lib.unc.edu/"
-
-_LICENSE = "CC BY 3.0"
-
-_URL = "https://cdr.lib.unc.edu/downloads/76537b20b?locale=en"
-
-
-class OnTheBooks(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.1.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "id": datasets.Value("string"),
-                "source": datasets.Value("string"),
-                "jim_crow": datasets.ClassLabel(names=["no_jim_crow", "jim_crow"]),
-                "type": datasets.Value("string"),
-                "chapter_num": datasets.Value("int32"),
-                "section_num": datasets.Value("int32"),
-                "chapter_text": datasets.Value("string"),
-                "section_text": datasets.Value("string"),
-            }
-        )
-
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-
-        data_file = dl_manager.download(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": data_file,
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples as (key, example) tuples."""
-        with open(filepath, encoding="utf-8") as f:
-            reader = csv.DictReader(f)
-            yield from enumerate(reader)