Hugging Face's logo

Datasets:
reglab
/
housing_qa

Tasks:
Question Answering
Languages:
English
Size:
1K<n<10K
Tags:
law
legal
retrieval
statutes
housing
QA
License:
Dataset card Files
xet
 Community
1
nguha commited on
Commit
3736c70
·
1 Parent(s): 9ab2868

Changed data

Browse files
Files changed (2) hide show
  1. housing_qa.py +29 -27
  2. statistics.ipynb +31 -26
housing_qa.py CHANGED
@@ -1,6 +1,7 @@
1
  import csv
2
 
3
  import datasets
 
4
  import json
5
  from io import StringIO
6
  from pathlib import Path
@@ -19,38 +20,39 @@ _CONFIGS = {}
19
 
20
  _CONFIGS["questions"] = {
21
  "description": "Questions about housing law.",
22
- "features": {
23
- "idx": datasets.Value("int32"),
24
- "state": datasets.Value("string"),
25
- "question": datasets.Value("string"),
26
- "answer": datasets.Value("string"),
27
- "question_group": datasets.Value("int32"),
28
- "statutes": {
29
- "statute_idx": datasets.Sequence(datasets.Value("int32")),
30
- "citation": datasets.Sequence(datasets.Value("string")),
31
- "excerpt": datasets.Sequence(datasets.Value("string")),
32
- },
33
- "original_question": datasets.Value("string"),
34
- "caveats": datasets.Sequence(datasets.Value("string")),
35
- },
 
36
  "license": None,
37
  }
38
 
39
  _CONFIGS["questions_aux"] = {
40
  "description": "An auxilliary set of larger questions about housing law, without statutory annotations.",
41
- "features": {
42
- "idx": datasets.Value("int32"),
43
- "state": datasets.Value("string"),
44
- "question": datasets.Value("string"),
45
- "answer": datasets.Value("string"),
46
- "question_group": datasets.Value("int32"),
47
- "statutes": {
48
- "citation": datasets.Sequence(datasets.Value("string")),
49
- "excerpt": datasets.Sequence(datasets.Value("string")),
50
- },
51
- "original_question": datasets.Value("string"),
52
- "caveats": datasets.Sequence(datasets.Value("string")),
53
- },
54
  "license": None,
55
  }
56
 
 
1
  import csv
2
 
3
  import datasets
4
+ from datasets import Features, Value, Sequence
5
  import json
6
  from io import StringIO
7
  from pathlib import Path
 
20
 
21
  _CONFIGS["questions"] = {
22
  "description": "Questions about housing law.",
23
+ "features": Features({
24
+ "idx": Value("int32"),
25
+ "state": Value("string"),
26
+ "question": Value("string"),
27
+ "answer": Value("string"),
28
+ "question_group": Value("int32"),
29
+ "statutes": Sequence({
30
+ "statute_idx": Value("int32"),
31
+ "citation": Value("string"),
32
+ "excerpt": Value("string")
33
+ }),
34
+ "original_question": Value("string"),
35
+ "caveats": Sequence(Value("string")),
36
+ }),
37
+ "license": None,
38
  "license": None,
39
  }
40
 
41
  _CONFIGS["questions_aux"] = {
42
  "description": "An auxilliary set of larger questions about housing law, without statutory annotations.",
43
+ "features": Features({
44
+ "idx": Value("int32"),
45
+ "state": Value("string"),
46
+ "question": Value("string"),
47
+ "answer": Value("string"),
48
+ "question_group": Value("int32"),
49
+ "statutes": Sequence({
50
+ "citation": Value("string"),
51
+ "excerpt": Value("string")
52
+ }),
53
+ "original_question": Value("string"),
54
+ "caveats": Sequence(Value("string")),
55
+ }),
56
  "license": None,
57
  }
58
 
statistics.ipynb CHANGED
@@ -2,7 +2,7 @@
2
  "cells": [
3
  {
4
  "cell_type": "code",
5
- "execution_count": 15,
6
  "id": "fce498ac-4ea7-4e10-a15a-60ac41e3adce",
7
  "metadata": {},
8
  "outputs": [],
@@ -13,53 +13,58 @@
13
  },
14
  {
15
  "cell_type": "code",
16
- "execution_count": 7,
17
  "id": "73aaafd1-3ebb-42f7-b162-2e6bc630d195",
18
  "metadata": {},
19
  "outputs": [
20
  {
21
- "name": "stdout",
22
  "output_type": "stream",
23
  "text": [
24
- "Downloading and preparing dataset housing_qa/rc_questions to /Users/neelguha/.cache/huggingface/datasets/reglab___housing_qa/rc_questions/1.0.0/cc9b072f76a495a77b95dea87f9dce53c85bad450eb9ac41c80026e7d4b0f08e...\n"
25
  ]
26
  },
27
  {
28
- "name": "stderr",
29
  "output_type": "stream",
30
  "text": [
31
- " \r"
32
  ]
33
  },
34
  {
35
- "name": "stdout",
36
  "output_type": "stream",
37
  "text": [
38
- "Dataset housing_qa downloaded and prepared to /Users/neelguha/.cache/huggingface/datasets/reglab___housing_qa/rc_questions/1.0.0/cc9b072f76a495a77b95dea87f9dce53c85bad450eb9ac41c80026e7d4b0f08e. Subsequent calls will reuse this data.\n"
 
39
  ]
40
  },
41
  {
42
- "data": {
43
- "text/plain": [
44
- "{'idx': 0,\n",
45
- " 'state': 'Alabama',\n",
46
- " 'question': 'Is there a state/territory law regulating residential evictions?',\n",
47
- " 'answer': 'Yes',\n",
48
- " 'question_group': 69,\n",
49
- " 'statutes': {'statute_idx': [431263],\n",
50
- " 'citation': ['ALA. CODE § 35-9A-141(11)'],\n",
51
- " 'excerpt': ['(11) “premises” means a dwelling unit and the structure of which it is a part and facilities and appurtenances therein and grounds, areas, and facilities held out for the use of tenants generally or whose use is promised by the rental agreement to the tenant;']},\n",
52
- " 'original_question': 'Is there a state/territory law regulating residential evictions?',\n",
53
- " 'caveats': [[]]}"
54
- ]
55
- },
56
- "execution_count": 7,
57
- "metadata": {},
58
- "output_type": "execute_result"
 
 
 
 
59
  }
60
  ],
61
  "source": [
62
- "questions = load_dataset(\"reglab/housing_qa\", \"rc_questions\", split=\"corpus\")\n",
63
  "questions[0]"
64
  ]
65
  },
 
2
  "cells": [
3
  {
4
  "cell_type": "code",
5
+ "execution_count": 20,
6
  "id": "fce498ac-4ea7-4e10-a15a-60ac41e3adce",
7
  "metadata": {},
8
  "outputs": [],
 
13
  },
14
  {
15
  "cell_type": "code",
16
+ "execution_count": 21,
17
  "id": "73aaafd1-3ebb-42f7-b162-2e6bc630d195",
18
  "metadata": {},
19
  "outputs": [
20
  {
21
+ "name": "stderr",
22
  "output_type": "stream",
23
  "text": [
24
+ "Downloading builder script: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.81k/3.81k [00:00<00:00, 7.26MB/s]\n"
25
  ]
26
  },
27
  {
28
+ "name": "stdout",
29
  "output_type": "stream",
30
  "text": [
31
+ "Downloading and preparing dataset housing_qa/questions to /Users/neelguha/.cache/huggingface/datasets/reglab___housing_qa/questions/1.0.0/a7e3a86df1ac2724d092acb7125993a634c6cb538dfbf6f5982b4b63171bee33...\n"
32
  ]
33
  },
34
  {
35
+ "name": "stderr",
36
  "output_type": "stream",
37
  "text": [
38
+ "Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 987k/987k [00:00<00:00, 11.4MB/s]\n",
39
+ " \r"
40
  ]
41
  },
42
  {
43
+ "ename": "TypeError",
44
+ "evalue": "list indices must be integers or slices, not str",
45
+ "output_type": "error",
46
+ "traceback": [
47
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
48
+ "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
49
+ "Cell \u001b[0;32mIn[21], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m questions \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mreglab/housing_qa\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mquestions\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msplit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtest\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m questions[\u001b[38;5;241m0\u001b[39m]\n",
50
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/load.py:1693\u001b[0m, in \u001b[0;36mload_dataset\u001b[0;34m(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)\u001b[0m\n\u001b[1;32m 1690\u001b[0m try_from_hf_gcs \u001b[38;5;241m=\u001b[39m path \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m _PACKAGED_DATASETS_MODULES\n\u001b[1;32m 1692\u001b[0m \u001b[38;5;66;03m# Download and prepare data\u001b[39;00m\n\u001b[0;32m-> 1693\u001b[0m \u001b[43mbuilder_instance\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdownload_and_prepare\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1694\u001b[0m \u001b[43m \u001b[49m\u001b[43mdownload_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1695\u001b[0m \u001b[43m \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1696\u001b[0m \u001b[43m \u001b[49m\u001b[43mignore_verifications\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mignore_verifications\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1697\u001b[0m \u001b[43m \u001b[49m\u001b[43mtry_from_hf_gcs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtry_from_hf_gcs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1698\u001b[0m \u001b[43m \u001b[49m\u001b[43muse_auth_token\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_auth_token\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1699\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1701\u001b[0m \u001b[38;5;66;03m# Build dataset for splits\u001b[39;00m\n\u001b[1;32m 1702\u001b[0m keep_in_memory \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 1703\u001b[0m keep_in_memory \u001b[38;5;28;01mif\u001b[39;00m keep_in_memory \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m is_small_dataset(builder_instance\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39mdataset_size)\n\u001b[1;32m 1704\u001b[0m )\n",
51
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/builder.py:807\u001b[0m, in \u001b[0;36mDatasetBuilder.download_and_prepare\u001b[0;34m(self, output_dir, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, file_format, max_shard_size, storage_options, **download_and_prepare_kwargs)\u001b[0m\n\u001b[1;32m 801\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m downloaded_from_gcs:\n\u001b[1;32m 802\u001b[0m prepare_split_kwargs \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 803\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfile_format\u001b[39m\u001b[38;5;124m\"\u001b[39m: file_format,\n\u001b[1;32m 804\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmax_shard_size\u001b[39m\u001b[38;5;124m\"\u001b[39m: max_shard_size,\n\u001b[1;32m 805\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mdownload_and_prepare_kwargs,\n\u001b[1;32m 806\u001b[0m }\n\u001b[0;32m--> 807\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_download_and_prepare\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 808\u001b[0m \u001b[43m \u001b[49m\u001b[43mdl_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdl_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 809\u001b[0m \u001b[43m \u001b[49m\u001b[43mverify_infos\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverify_infos\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 810\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mprepare_split_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 811\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdownload_and_prepare_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 812\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 813\u001b[0m \u001b[38;5;66;03m# Sync info\u001b[39;00m\n\u001b[1;32m 814\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39mdataset_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msum\u001b[39m(split\u001b[38;5;241m.\u001b[39mnum_bytes \u001b[38;5;28;01mfor\u001b[39;00m split \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39msplits\u001b[38;5;241m.\u001b[39mvalues())\n",
52
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/builder.py:1416\u001b[0m, in \u001b[0;36mGeneratorBasedBuilder._download_and_prepare\u001b[0;34m(self, dl_manager, verify_infos, **prepare_splits_kwargs)\u001b[0m\n\u001b[1;32m 1415\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_download_and_prepare\u001b[39m(\u001b[38;5;28mself\u001b[39m, dl_manager, verify_infos, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mprepare_splits_kwargs):\n\u001b[0;32m-> 1416\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_download_and_prepare\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1417\u001b[0m \u001b[43m \u001b[49m\u001b[43mdl_manager\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverify_infos\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcheck_duplicate_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverify_infos\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mprepare_splits_kwargs\u001b[49m\n\u001b[1;32m 1418\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
53
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/builder.py:898\u001b[0m, in \u001b[0;36mDatasetBuilder._download_and_prepare\u001b[0;34m(self, dl_manager, verify_infos, **prepare_split_kwargs)\u001b[0m\n\u001b[1;32m 894\u001b[0m split_dict\u001b[38;5;241m.\u001b[39madd(split_generator\u001b[38;5;241m.\u001b[39msplit_info)\n\u001b[1;32m 896\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 897\u001b[0m \u001b[38;5;66;03m# Prepare split will record examples associated to the split\u001b[39;00m\n\u001b[0;32m--> 898\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_prepare_split\u001b[49m\u001b[43m(\u001b[49m\u001b[43msplit_generator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mprepare_split_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 899\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 900\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m(\n\u001b[1;32m 901\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot find data file. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 902\u001b[0m \u001b[38;5;241m+\u001b[39m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmanual_download_instructions \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 903\u001b[0m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mOriginal error:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 904\u001b[0m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mstr\u001b[39m(e)\n\u001b[1;32m 905\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
54
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/builder.py:1390\u001b[0m, in \u001b[0;36mGeneratorBasedBuilder._prepare_split\u001b[0;34m(self, split_generator, check_duplicate_keys, file_format, max_shard_size)\u001b[0m\n\u001b[1;32m 1380\u001b[0m shard_id \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 1381\u001b[0m writer \u001b[38;5;241m=\u001b[39m writer_class(\n\u001b[1;32m 1382\u001b[0m features\u001b[38;5;241m=\u001b[39mwriter\u001b[38;5;241m.\u001b[39m_features,\n\u001b[1;32m 1383\u001b[0m path\u001b[38;5;241m=\u001b[39mfpath\u001b[38;5;241m.\u001b[39mreplace(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSSSSS\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mshard_id\u001b[38;5;132;01m:\u001b[39;00m\u001b[38;5;124m05d\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m),\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1388\u001b[0m embed_local_files\u001b[38;5;241m=\u001b[39membed_local_files,\n\u001b[1;32m 1389\u001b[0m )\n\u001b[0;32m-> 1390\u001b[0m example \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minfo\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfeatures\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencode_example\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrecord\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39mfeatures \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m record\n\u001b[1;32m 1391\u001b[0m writer\u001b[38;5;241m.\u001b[39mwrite(example, key)\n\u001b[1;32m 1392\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
55
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/features/features.py:1614\u001b[0m, in \u001b[0;36mFeatures.encode_example\u001b[0;34m(self, example)\u001b[0m\n\u001b[1;32m 1604\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1605\u001b[0m \u001b[38;5;124;03mEncode example into a format for Arrow.\u001b[39;00m\n\u001b[1;32m 1606\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1611\u001b[0m \u001b[38;5;124;03m :obj:`dict[str, Any]`\u001b[39;00m\n\u001b[1;32m 1612\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1613\u001b[0m example \u001b[38;5;241m=\u001b[39m cast_to_python_objects(example)\n\u001b[0;32m-> 1614\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mencode_nested_example\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexample\u001b[49m\u001b[43m)\u001b[49m\n",
56
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/features/features.py:1165\u001b[0m, in \u001b[0;36mencode_nested_example\u001b[0;34m(schema, obj, level)\u001b[0m\n\u001b[1;32m 1162\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m obj \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1163\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mGot None but expected a dictionary instead\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\n\u001b[0;32m-> 1165\u001b[0m {\n\u001b[1;32m 1166\u001b[0m k: encode_nested_example(sub_schema, sub_obj, level\u001b[38;5;241m=\u001b[39mlevel \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m 1167\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m k, (sub_schema, sub_obj) \u001b[38;5;129;01min\u001b[39;00m zip_dict(schema, obj)\n\u001b[1;32m 1168\u001b[0m }\n\u001b[1;32m 1169\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m obj \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1170\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1171\u001b[0m )\n\u001b[1;32m 1173\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(schema, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m)):\n\u001b[1;32m 1174\u001b[0m sub_schema \u001b[38;5;241m=\u001b[39m schema[\u001b[38;5;241m0\u001b[39m]\n",
57
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/features/features.py:1166\u001b[0m, in \u001b[0;36m<dictcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 1162\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m obj \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1163\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mGot None but expected a dictionary instead\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\n\u001b[1;32m 1165\u001b[0m {\n\u001b[0;32m-> 1166\u001b[0m k: \u001b[43mencode_nested_example\u001b[49m\u001b[43m(\u001b[49m\u001b[43msub_schema\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msub_obj\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1167\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m k, (sub_schema, sub_obj) \u001b[38;5;129;01min\u001b[39;00m zip_dict(schema, obj)\n\u001b[1;32m 1168\u001b[0m }\n\u001b[1;32m 1169\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m obj \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1170\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1171\u001b[0m )\n\u001b[1;32m 1173\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(schema, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m)):\n\u001b[1;32m 1174\u001b[0m sub_schema \u001b[38;5;241m=\u001b[39m schema[\u001b[38;5;241m0\u001b[39m]\n",
58
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/features/features.py:1165\u001b[0m, in \u001b[0;36mencode_nested_example\u001b[0;34m(schema, obj, level)\u001b[0m\n\u001b[1;32m 1162\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m obj \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1163\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mGot None but expected a dictionary instead\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\n\u001b[0;32m-> 1165\u001b[0m {\n\u001b[1;32m 1166\u001b[0m k: encode_nested_example(sub_schema, sub_obj, level\u001b[38;5;241m=\u001b[39mlevel \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m 1167\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m k, (sub_schema, sub_obj) \u001b[38;5;129;01min\u001b[39;00m zip_dict(schema, obj)\n\u001b[1;32m 1168\u001b[0m }\n\u001b[1;32m 1169\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m obj \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1170\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1171\u001b[0m )\n\u001b[1;32m 1173\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(schema, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m)):\n\u001b[1;32m 1174\u001b[0m sub_schema \u001b[38;5;241m=\u001b[39m schema[\u001b[38;5;241m0\u001b[39m]\n",
59
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/features/features.py:1165\u001b[0m, in \u001b[0;36m<dictcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 1162\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m obj \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1163\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mGot None but expected a dictionary instead\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\n\u001b[0;32m-> 1165\u001b[0m {\n\u001b[1;32m 1166\u001b[0m k: encode_nested_example(sub_schema, sub_obj, level\u001b[38;5;241m=\u001b[39mlevel \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m 1167\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m k, (sub_schema, sub_obj) \u001b[38;5;129;01min\u001b[39;00m zip_dict(schema, obj)\n\u001b[1;32m 1168\u001b[0m }\n\u001b[1;32m 1169\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m obj \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1170\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1171\u001b[0m )\n\u001b[1;32m 1173\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(schema, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m)):\n\u001b[1;32m 1174\u001b[0m sub_schema \u001b[38;5;241m=\u001b[39m schema[\u001b[38;5;241m0\u001b[39m]\n",
60
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/utils/py_utils.py:286\u001b[0m, in \u001b[0;36mzip_dict\u001b[0;34m(*dicts)\u001b[0m\n\u001b[1;32m 283\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Iterate over items of dictionaries grouped by their keys.\"\"\"\u001b[39;00m\n\u001b[1;32m 284\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m key \u001b[38;5;129;01min\u001b[39;00m unique_values(itertools\u001b[38;5;241m.\u001b[39mchain(\u001b[38;5;241m*\u001b[39mdicts)): \u001b[38;5;66;03m# set merge all keys\u001b[39;00m\n\u001b[1;32m 285\u001b[0m \u001b[38;5;66;03m# Will raise KeyError if the dict don't have the same keys\u001b[39;00m\n\u001b[0;32m--> 286\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m key, \u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43md\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43md\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mdicts\u001b[49m\u001b[43m)\u001b[49m\n",
61
+ "File \u001b[0;32m~/miniconda3/envs/judicial-behavior/lib/python3.8/site-packages/datasets/utils/py_utils.py:286\u001b[0m, in \u001b[0;36m<genexpr>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 283\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Iterate over items of dictionaries grouped by their keys.\"\"\"\u001b[39;00m\n\u001b[1;32m 284\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m key \u001b[38;5;129;01min\u001b[39;00m unique_values(itertools\u001b[38;5;241m.\u001b[39mchain(\u001b[38;5;241m*\u001b[39mdicts)): \u001b[38;5;66;03m# set merge all keys\u001b[39;00m\n\u001b[1;32m 285\u001b[0m \u001b[38;5;66;03m# Will raise KeyError if the dict don't have the same keys\u001b[39;00m\n\u001b[0;32m--> 286\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m key, \u001b[38;5;28mtuple\u001b[39m(\u001b[43md\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m]\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m d \u001b[38;5;129;01min\u001b[39;00m dicts)\n",
62
+ "\u001b[0;31mTypeError\u001b[0m: list indices must be integers or slices, not str"
63
+ ]
64
  }
65
  ],
66
  "source": [
67
+ "questions = load_dataset(\"reglab/housing_qa\", \"questions\", split=\"test\")\n",
68
  "questions[0]"
69
  ]
70
  },