draft

README.md

@@ -1,3 +1,31 @@
 ---
 license: cc-by-3.0
+dataset_info:
+  features:
+  - name: id
+    dtype: string
+  - name: source
+    dtype: string
+  - name: jim_crow
+    dtype:
+      class_label:
+        names:
+          '0': no_jim_crow
+          '1': jim_crow
+  - name: type
+    dtype: string
+  - name: chapter_num
+    dtype: int32
+  - name: section_num
+    dtype: int32
+  - name: chapter_text
+    dtype: string
+  - name: section_text
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 2119395
+    num_examples: 1785
+  download_size: 2085196
+  dataset_size: 2119395
 ---

on_the_books.py

@@ -0,0 +1,81 @@
+# 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/2"
+
+_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)