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Datasets:
GEM
/
sportsett_basketball

Tasks:
Table to Text
Modalities:
Text
Languages:
English
Size:
1K - 10K
Tags:
data-to-text
Libraries:
Datasets
License:
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  1. sportsett_basketball_new.py +0 -584
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- # coding=utf-8
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- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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- """TODO: Add a description here."""
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-
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-
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- import csv
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- import json
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- import os
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-
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- import datasets
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-
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-
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- # TODO: Add BibTeX citation
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- # Find for instance the citation on arxiv or on the dataset repo/website
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- _CITATION = """\
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- @inproceedings{thomson-etal-2020-sportsett,
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- title = "{S}port{S}ett:Basketball - A robust and maintainable data-set for Natural Language Generation",
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- author = "Thomson, Craig and
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- Reiter, Ehud and
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- Sripada, Somayajulu",
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- booktitle = "Proceedings of the Workshop on Intelligent Information Processing and Natural Language Generation",
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- month = sep,
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- year = "2020",
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- address = "Santiago de Compostela, Spain",
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- publisher = "Association for Computational Lingustics",
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- url = "https://aclanthology.org/2020.intellang-1.4",
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- pages = "32--40",
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- }
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- """
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-
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- # TODO: Add description of the dataset here
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- # You can copy an official description
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- _DESCRIPTION = """\
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- SportSett:Basketball dataset for Data-to-Text Generation contains NBA games stats aligned with their human written summaries.
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- """
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-
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- # TODO: Add a link to an official homepage for the dataset here
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- _HOMEPAGE = "https://github.com/nlgcat/sport_sett_basketball"
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-
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- # TODO: Add the licence for the dataset here if you can find it
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- _LICENSE = ""
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-
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- # TODO: Add link to the official dataset URLs here
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- # The HuggingFace dataset library don't host the datasets but only point to the original files
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- # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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- _URLs = {
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- "train": "train.json",
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- "validation": "validation.json",
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- "test": "test.json"
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- }
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-
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-
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- # TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
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- class SportSettBasketball(datasets.GeneratorBasedBuilder):
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- """SportSett:Basketball datatset for Data-to-Text Generation."""
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-
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- VERSION = datasets.Version("1.1.0")
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-
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- def _info(self):
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- features = datasets.Features(
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- {
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- "sportsett_id": datasets.Value("string"),
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- "gem_id": datasets.Value("string"),
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- "game": {
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- "day": datasets.Value("string"),
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- "month": datasets.Value("string"),
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- "year": datasets.Value("string"),
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- "dayname": datasets.Value("string"),
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- "season": datasets.Value("string"),
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- "stadium": datasets.Value("string"),
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- "city": datasets.Value("string"),
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- "state": datasets.Value("string"),
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- "attendance": datasets.Value("string"),
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- "capacity": datasets.Value("string"),
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- "game_id": datasets.Value("string")
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- },
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- "teams": {
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- "home": {
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- "name": datasets.Value("string"),
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- "place": datasets.Value("string"),
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- "conference": datasets.Value("string"),
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- "division": datasets.Value("string"),
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- "wins": datasets.Value("string"),
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- "losses": datasets.Value("string"),
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- "conference_standing": datasets.Value("int32"),
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- "game_number": datasets.Value("string"),
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- "previous_game_id": datasets.Value("string"),
100
- "next_game_id": datasets.Value("string"),
101
- "line_score": {
102
- "game": {
103
- "FG3A": datasets.Value("string"),
104
- "FG3M": datasets.Value("string"),
105
- "FG3_PCT": datasets.Value("string"),
106
- "FGA": datasets.Value("string"),
107
- "FGM": datasets.Value("string"),
108
- "FG_PCT": datasets.Value("string"),
109
- "FTA": datasets.Value("string"),
110
- "FTM": datasets.Value("string"),
111
- "FT_PCT": datasets.Value("string"),
112
- "DREB": datasets.Value("string"),
113
- "OREB": datasets.Value("string"),
114
- "TREB": datasets.Value("string"),
115
- "BLK": datasets.Value("string"),
116
- "AST": datasets.Value("string"),
117
- "STL": datasets.Value("string"),
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- "TOV": datasets.Value("string"),
119
- "PF": datasets.Value("string"),
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- "PTS": datasets.Value("string"),
121
- "MIN": datasets.Value("string")
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- },
123
- "H1": {
124
- "FG3A": datasets.Value("string"),
125
- "FG3M": datasets.Value("string"),
126
- "FG3_PCT": datasets.Value("string"),
127
- "FGA": datasets.Value("string"),
128
- "FGM": datasets.Value("string"),
129
- "FG_PCT": datasets.Value("string"),
130
- "FTA": datasets.Value("string"),
131
- "FTM": datasets.Value("string"),
132
- "FT_PCT": datasets.Value("string"),
133
- "DREB": datasets.Value("string"),
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- "OREB": datasets.Value("string"),
135
- "TREB": datasets.Value("string"),
136
- "BLK": datasets.Value("string"),
137
- "AST": datasets.Value("string"),
138
- "STL": datasets.Value("string"),
139
- "TOV": datasets.Value("string"),
140
- "PTS": datasets.Value("string"),
141
- "MIN": datasets.Value("string")
142
- },
143
- "H2": {
144
- "FG3A": datasets.Value("string"),
145
- "FG3M": datasets.Value("string"),
146
- "FG3_PCT": datasets.Value("string"),
147
- "FGA": datasets.Value("string"),
148
- "FGM": datasets.Value("string"),
149
- "FG_PCT": datasets.Value("string"),
150
- "FTA": datasets.Value("string"),
151
- "FTM": datasets.Value("string"),
152
- "FT_PCT": datasets.Value("string"),
153
- "DREB": datasets.Value("string"),
154
- "OREB": datasets.Value("string"),
155
- "TREB": datasets.Value("string"),
156
- "BLK": datasets.Value("string"),
157
- "AST": datasets.Value("string"),
158
- "STL": datasets.Value("string"),
159
- "TOV": datasets.Value("string"),
160
- "PTS": datasets.Value("string"),
161
- "MIN": datasets.Value("string")
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- },
163
- "Q1": {
164
- "FG3A": datasets.Value("string"),
165
- "FG3M": datasets.Value("string"),
166
- "FG3_PCT": datasets.Value("string"),
167
- "FGA": datasets.Value("string"),
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- "FGM": datasets.Value("string"),
169
- "FG_PCT": datasets.Value("string"),
170
- "FTA": datasets.Value("string"),
171
- "FTM": datasets.Value("string"),
172
- "FT_PCT": datasets.Value("string"),
173
- "DREB": datasets.Value("string"),
174
- "OREB": datasets.Value("string"),
175
- "TREB": datasets.Value("string"),
176
- "BLK": datasets.Value("string"),
177
- "AST": datasets.Value("string"),
178
- "STL": datasets.Value("string"),
179
- "TOV": datasets.Value("string"),
180
- "PTS": datasets.Value("string"),
181
- "MIN": datasets.Value("string")
182
- },
183
- "Q2": {
184
- "FG3A": datasets.Value("string"),
185
- "FG3M": datasets.Value("string"),
186
- "FG3_PCT": datasets.Value("string"),
187
- "FGA": datasets.Value("string"),
188
- "FGM": datasets.Value("string"),
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- "FG_PCT": datasets.Value("string"),
190
- "FTA": datasets.Value("string"),
191
- "FTM": datasets.Value("string"),
192
- "FT_PCT": datasets.Value("string"),
193
- "DREB": datasets.Value("string"),
194
- "OREB": datasets.Value("string"),
195
- "TREB": datasets.Value("string"),
196
- "BLK": datasets.Value("string"),
197
- "AST": datasets.Value("string"),
198
- "STL": datasets.Value("string"),
199
- "TOV": datasets.Value("string"),
200
- "PTS": datasets.Value("string"),
201
- "MIN": datasets.Value("string")
202
- },
203
- "Q3": {
204
- "FG3A": datasets.Value("string"),
205
- "FG3M": datasets.Value("string"),
206
- "FG3_PCT": datasets.Value("string"),
207
- "FGA": datasets.Value("string"),
208
- "FGM": datasets.Value("string"),
209
- "FG_PCT": datasets.Value("string"),
210
- "FTA": datasets.Value("string"),
211
- "FTM": datasets.Value("string"),
212
- "FT_PCT": datasets.Value("string"),
213
- "DREB": datasets.Value("string"),
214
- "OREB": datasets.Value("string"),
215
- "TREB": datasets.Value("string"),
216
- "BLK": datasets.Value("string"),
217
- "AST": datasets.Value("string"),
218
- "STL": datasets.Value("string"),
219
- "TOV": datasets.Value("string"),
220
- "PTS": datasets.Value("string"),
221
- "MIN": datasets.Value("string")
222
- },
223
- "Q4": {
224
- "FG3A": datasets.Value("string"),
225
- "FG3M": datasets.Value("string"),
226
- "FG3_PCT": datasets.Value("string"),
227
- "FGA": datasets.Value("string"),
228
- "FGM": datasets.Value("string"),
229
- "FG_PCT": datasets.Value("string"),
230
- "FTA": datasets.Value("string"),
231
- "FTM": datasets.Value("string"),
232
- "FT_PCT": datasets.Value("string"),
233
- "DREB": datasets.Value("string"),
234
- "OREB": datasets.Value("string"),
235
- "TREB": datasets.Value("string"),
236
- "BLK": datasets.Value("string"),
237
- "AST": datasets.Value("string"),
238
- "STL": datasets.Value("string"),
239
- "TOV": datasets.Value("string"),
240
- "PTS": datasets.Value("string"),
241
- "MIN": datasets.Value("string")
242
- },
243
- "OT": {
244
- "FG3A": datasets.Value("string"),
245
- "FG3M": datasets.Value("string"),
246
- "FG3_PCT": datasets.Value("string"),
247
- "FGA": datasets.Value("string"),
248
- "FGM": datasets.Value("string"),
249
- "FG_PCT": datasets.Value("string"),
250
- "FTA": datasets.Value("string"),
251
- "FTM": datasets.Value("string"),
252
- "FT_PCT": datasets.Value("string"),
253
- "DREB": datasets.Value("string"),
254
- "OREB": datasets.Value("string"),
255
- "TREB": datasets.Value("string"),
256
- "BLK": datasets.Value("string"),
257
- "AST": datasets.Value("string"),
258
- "STL": datasets.Value("string"),
259
- "TOV": datasets.Value("string"),
260
- "PTS": datasets.Value("string"),
261
- "MIN": datasets.Value("string")
262
- }
263
- },
264
- "box_score": [
265
- {
266
- "first_name": datasets.Value("string"),
267
- "last_name": datasets.Value("string"),
268
- "name": datasets.Value("string"),
269
- "starter": datasets.Value("string"),
270
- "MIN": datasets.Value("string"),
271
- "FGM": datasets.Value("string"),
272
- "FGA": datasets.Value("string"),
273
- "FG_PCT": datasets.Value("string"),
274
- "FG3M": datasets.Value("string"),
275
- "FG3A": datasets.Value("string"),
276
- "FG3_PCT": datasets.Value("string"),
277
- "FTM": datasets.Value("string"),
278
- "FTA": datasets.Value("string"),
279
- "FT_PCT": datasets.Value("string"),
280
- "OREB": datasets.Value("string"),
281
- "DREB": datasets.Value("string"),
282
- "TREB": datasets.Value("string"),
283
- "AST": datasets.Value("string"),
284
- "STL": datasets.Value("string"),
285
- "BLK": datasets.Value("string"),
286
- "TOV": datasets.Value("string"),
287
- "PF": datasets.Value("string"),
288
- "PTS": datasets.Value("string"),
289
- "+/-": datasets.Value("string"),
290
- "DOUBLE": datasets.Value("string")
291
- }
292
- ],
293
- "next_game": {
294
- "day": datasets.Value("string"),
295
- "month": datasets.Value("string"),
296
- "year": datasets.Value("string"),
297
- "dayname": datasets.Value("string"),
298
- "stadium": datasets.Value("string"),
299
- "city": datasets.Value("string"),
300
- "opponent_name": datasets.Value("string"),
301
- "opponent_place": datasets.Value("string"),
302
- "is_home": datasets.Value("string"),
303
- }
304
- },
305
- "vis": {
306
- "name": datasets.Value("string"),
307
- "place": datasets.Value("string"),
308
- "conference": datasets.Value("string"),
309
- "division": datasets.Value("string"),
310
- "wins": datasets.Value("string"),
311
- "losses": datasets.Value("string"),
312
- "conference_standing": datasets.Value("int32"),
313
- "game_number": datasets.Value("string"),
314
- "previous_game_id": datasets.Value("string"),
315
- "next_game_id": datasets.Value("string"),
316
- "line_score": {
317
- "game": {
318
- "FG3A": datasets.Value("string"),
319
- "FG3M": datasets.Value("string"),
320
- "FG3_PCT": datasets.Value("string"),
321
- "FGA": datasets.Value("string"),
322
- "FGM": datasets.Value("string"),
323
- "FG_PCT": datasets.Value("string"),
324
- "FTA": datasets.Value("string"),
325
- "FTM": datasets.Value("string"),
326
- "FT_PCT": datasets.Value("string"),
327
- "DREB": datasets.Value("string"),
328
- "OREB": datasets.Value("string"),
329
- "TREB": datasets.Value("string"),
330
- "BLK": datasets.Value("string"),
331
- "AST": datasets.Value("string"),
332
- "STL": datasets.Value("string"),
333
- "TOV": datasets.Value("string"),
334
- "PF": datasets.Value("string"),
335
- "PTS": datasets.Value("string"),
336
- "MIN": datasets.Value("string")
337
- },
338
- "H1": {
339
- "FG3A": datasets.Value("string"),
340
- "FG3M": datasets.Value("string"),
341
- "FG3_PCT": datasets.Value("string"),
342
- "FGA": datasets.Value("string"),
343
- "FGM": datasets.Value("string"),
344
- "FG_PCT": datasets.Value("string"),
345
- "FTA": datasets.Value("string"),
346
- "FTM": datasets.Value("string"),
347
- "FT_PCT": datasets.Value("string"),
348
- "DREB": datasets.Value("string"),
349
- "OREB": datasets.Value("string"),
350
- "TREB": datasets.Value("string"),
351
- "BLK": datasets.Value("string"),
352
- "AST": datasets.Value("string"),
353
- "STL": datasets.Value("string"),
354
- "TOV": datasets.Value("string"),
355
- "PTS": datasets.Value("string"),
356
- "MIN": datasets.Value("string")
357
- },
358
- "H2": {
359
- "FG3A": datasets.Value("string"),
360
- "FG3M": datasets.Value("string"),
361
- "FG3_PCT": datasets.Value("string"),
362
- "FGA": datasets.Value("string"),
363
- "FGM": datasets.Value("string"),
364
- "FG_PCT": datasets.Value("string"),
365
- "FTA": datasets.Value("string"),
366
- "FTM": datasets.Value("string"),
367
- "FT_PCT": datasets.Value("string"),
368
- "DREB": datasets.Value("string"),
369
- "OREB": datasets.Value("string"),
370
- "TREB": datasets.Value("string"),
371
- "BLK": datasets.Value("string"),
372
- "AST": datasets.Value("string"),
373
- "STL": datasets.Value("string"),
374
- "TOV": datasets.Value("string"),
375
- "PTS": datasets.Value("string"),
376
- "MIN": datasets.Value("string")
377
- },
378
- "Q1": {
379
- "FG3A": datasets.Value("string"),
380
- "FG3M": datasets.Value("string"),
381
- "FG3_PCT": datasets.Value("string"),
382
- "FGA": datasets.Value("string"),
383
- "FGM": datasets.Value("string"),
384
- "FG_PCT": datasets.Value("string"),
385
- "FTA": datasets.Value("string"),
386
- "FTM": datasets.Value("string"),
387
- "FT_PCT": datasets.Value("string"),
388
- "DREB": datasets.Value("string"),
389
- "OREB": datasets.Value("string"),
390
- "TREB": datasets.Value("string"),
391
- "BLK": datasets.Value("string"),
392
- "AST": datasets.Value("string"),
393
- "STL": datasets.Value("string"),
394
- "TOV": datasets.Value("string"),
395
- "PTS": datasets.Value("string"),
396
- "MIN": datasets.Value("string")
397
- },
398
- "Q2": {
399
- "FG3A": datasets.Value("string"),
400
- "FG3M": datasets.Value("string"),
401
- "FG3_PCT": datasets.Value("string"),
402
- "FGA": datasets.Value("string"),
403
- "FGM": datasets.Value("string"),
404
- "FG_PCT": datasets.Value("string"),
405
- "FTA": datasets.Value("string"),
406
- "FTM": datasets.Value("string"),
407
- "FT_PCT": datasets.Value("string"),
408
- "DREB": datasets.Value("string"),
409
- "OREB": datasets.Value("string"),
410
- "TREB": datasets.Value("string"),
411
- "BLK": datasets.Value("string"),
412
- "AST": datasets.Value("string"),
413
- "STL": datasets.Value("string"),
414
- "TOV": datasets.Value("string"),
415
- "PTS": datasets.Value("string"),
416
- "MIN": datasets.Value("string")
417
- },
418
- "Q3": {
419
- "FG3A": datasets.Value("string"),
420
- "FG3M": datasets.Value("string"),
421
- "FG3_PCT": datasets.Value("string"),
422
- "FGA": datasets.Value("string"),
423
- "FGM": datasets.Value("string"),
424
- "FG_PCT": datasets.Value("string"),
425
- "FTA": datasets.Value("string"),
426
- "FTM": datasets.Value("string"),
427
- "FT_PCT": datasets.Value("string"),
428
- "DREB": datasets.Value("string"),
429
- "OREB": datasets.Value("string"),
430
- "TREB": datasets.Value("string"),
431
- "BLK": datasets.Value("string"),
432
- "AST": datasets.Value("string"),
433
- "STL": datasets.Value("string"),
434
- "TOV": datasets.Value("string"),
435
- "PTS": datasets.Value("string"),
436
- "MIN": datasets.Value("string")
437
- },
438
- "Q4": {
439
- "FG3A": datasets.Value("string"),
440
- "FG3M": datasets.Value("string"),
441
- "FG3_PCT": datasets.Value("string"),
442
- "FGA": datasets.Value("string"),
443
- "FGM": datasets.Value("string"),
444
- "FG_PCT": datasets.Value("string"),
445
- "FTA": datasets.Value("string"),
446
- "FTM": datasets.Value("string"),
447
- "FT_PCT": datasets.Value("string"),
448
- "DREB": datasets.Value("string"),
449
- "OREB": datasets.Value("string"),
450
- "TREB": datasets.Value("string"),
451
- "BLK": datasets.Value("string"),
452
- "AST": datasets.Value("string"),
453
- "STL": datasets.Value("string"),
454
- "TOV": datasets.Value("string"),
455
- "PTS": datasets.Value("string"),
456
- "MIN": datasets.Value("string")
457
- },
458
- "OT": {
459
- "FG3A": datasets.Value("string"),
460
- "FG3M": datasets.Value("string"),
461
- "FG3_PCT": datasets.Value("string"),
462
- "FGA": datasets.Value("string"),
463
- "FGM": datasets.Value("string"),
464
- "FG_PCT": datasets.Value("string"),
465
- "FTA": datasets.Value("string"),
466
- "FTM": datasets.Value("string"),
467
- "FT_PCT": datasets.Value("string"),
468
- "DREB": datasets.Value("string"),
469
- "OREB": datasets.Value("string"),
470
- "TREB": datasets.Value("string"),
471
- "BLK": datasets.Value("string"),
472
- "AST": datasets.Value("string"),
473
- "STL": datasets.Value("string"),
474
- "TOV": datasets.Value("string"),
475
- "PTS": datasets.Value("string"),
476
- "MIN": datasets.Value("string")
477
- }
478
- },
479
- "box_score": [
480
- {
481
- "first_name": datasets.Value("string"),
482
- "last_name": datasets.Value("string"),
483
- "name": datasets.Value("string"),
484
- "starter": datasets.Value("string"),
485
- "MIN": datasets.Value("string"),
486
- "FGM": datasets.Value("string"),
487
- "FGA": datasets.Value("string"),
488
- "FG_PCT": datasets.Value("string"),
489
- "FG3M": datasets.Value("string"),
490
- "FG3A": datasets.Value("string"),
491
- "FG3_PCT": datasets.Value("string"),
492
- "FTM": datasets.Value("string"),
493
- "FTA": datasets.Value("string"),
494
- "FT_PCT": datasets.Value("string"),
495
- "OREB": datasets.Value("string"),
496
- "DREB": datasets.Value("string"),
497
- "TREB": datasets.Value("string"),
498
- "AST": datasets.Value("string"),
499
- "STL": datasets.Value("string"),
500
- "BLK": datasets.Value("string"),
501
- "TOV": datasets.Value("string"),
502
- "PF": datasets.Value("string"),
503
- "PTS": datasets.Value("string"),
504
- "+/-": datasets.Value("string"),
505
- "DOUBLE": datasets.Value("string")
506
- }
507
- ],
508
- "next_game": {
509
- "day": datasets.Value("string"),
510
- "month": datasets.Value("string"),
511
- "year": datasets.Value("string"),
512
- "dayname": datasets.Value("string"),
513
- "stadium": datasets.Value("string"),
514
- "city": datasets.Value("string"),
515
- "opponent_name": datasets.Value("string"),
516
- "opponent_place": datasets.Value("string"),
517
- "is_home": datasets.Value("string"),
518
- }
519
- }
520
- },
521
- "summaries": datasets.Sequence(datasets.Value("string")),
522
- }
523
- )
524
- return datasets.DatasetInfo(
525
- description=_DESCRIPTION,
526
- features=features,
527
- supervised_keys=None,
528
- homepage=_HOMEPAGE,
529
- license=_LICENSE,
530
- citation=_CITATION,
531
- )
532
-
533
- def _split_generators(self, dl_manager):
534
- """Returns SplitGenerators."""
535
- # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
536
- # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
537
-
538
- # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
539
- # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
540
- # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
541
- data_dir = dl_manager.download_and_extract(_URLs)
542
- return [
543
- datasets.SplitGenerator(
544
- name=datasets.Split.TRAIN,
545
- # These kwargs will be passed to _generate_examples
546
- gen_kwargs={
547
- "filepath": data_dir["train"],
548
- "split": "train",
549
- },
550
- ),
551
- datasets.SplitGenerator(
552
- name=datasets.Split.TEST,
553
- # These kwargs will be passed to _generate_examples
554
- gen_kwargs={
555
- "filepath": data_dir["test"],
556
- "split": "test"
557
- },
558
- ),
559
- datasets.SplitGenerator(
560
- name=datasets.Split.VALIDATION,
561
- # These kwargs will be passed to _generate_examples
562
- gen_kwargs={
563
- "filepath": data_dir["validation"],
564
- "split": "validation",
565
- },
566
- ),
567
- ]
568
-
569
- def _generate_examples(
570
- self, filepath, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
571
- ):
572
- """ Yields examples as (key, example) tuples. """
573
- # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
574
- # The `key` is here for legacy reason (tfds) and is not important in itself.
575
-
576
- js = json.load(open(filepath, encoding="utf-8"))
577
- for id_, data in enumerate(js):
578
- yield id_, {
579
- "sportsett_id": data["sportsett_id"],
580
- "gem_id": data["gem_id"],
581
- "game": data["game"],
582
- "teams": data["teams"],
583
- "summaries": data["summaries"],
584
- }