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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError Exception: DatasetGenerationCastError Message: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 7 new columns ({'datetime', 'stationname', 'stationcode', 'value', 'municipality_id', 'sensordescription', 'measureunit'}) and 7 missing columns ({'date_event', 'place_id', 'taxonomy_id', 'registered_by', 'elevation_m', 'code_record', 'common_name'}). This happened while the csv dataset builder was generating data using hf://datasets/juanpac96/urban_tree_census_data/climate.csv (at revision f87ba58bace16cbd9f4a48273f8a0728df6053a1) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations) Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 623, in write_table pa_table = table_cast(pa_table, self._schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2293, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast municipality_id: int64 stationcode: int64 stationname: string datetime: string latitude: double longitude: double sensordescription: string measureunit: string value: double -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1350 to {'code_record': Value(dtype='int64', id=None), 'common_name': Value(dtype='string', id=None), 'latitude': Value(dtype='float64', id=None), 'longitude': Value(dtype='float64', id=None), 'elevation_m': Value(dtype='float64', id=None), 'registered_by': Value(dtype='string', id=None), 'date_event': Value(dtype='string', id=None), 'place_id': Value(dtype='int64', id=None), 'taxonomy_id': Value(dtype='int64', id=None)} because column names don't match During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1438, in compute_config_parquet_and_info_response parquet_operations = convert_to_parquet(builder) File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1050, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 925, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1001, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1873, in _prepare_split_single raise DatasetGenerationCastError.from_cast_error( datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 7 new columns ({'datetime', 'stationname', 'stationcode', 'value', 'municipality_id', 'sensordescription', 'measureunit'}) and 7 missing columns ({'date_event', 'place_id', 'taxonomy_id', 'registered_by', 'elevation_m', 'code_record', 'common_name'}). This happened while the csv dataset builder was generating data using hf://datasets/juanpac96/urban_tree_census_data/climate.csv (at revision f87ba58bace16cbd9f4a48273f8a0728df6053a1) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
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code_record
int64 | common_name
string | latitude
float64 | longitude
float64 | elevation_m
float64 | registered_by
string | date_event
string | place_id
int64 | taxonomy_id
int64 |
---|---|---|---|---|---|---|---|---|
1 | Gmelina melina | 4.407358 | -75.143061 | 939 | Cortolima | 2017-09-30 08:58:15 | 495 | 197 |
2 | Gmelina melina | 4.407582 | -75.14304 | 939 | Cortolima | 2017-09-30 08:54:56 | 495 | 197 |
3 | Gmelina melina | 4.407822 | -75.142962 | 939 | Cortolima | 2017-09-30 08:51:43 | 495 | 197 |
4 | Gmelina melina | 4.407983 | -75.142962 | 937 | Cortolima | 2017-09-30 08:49:51 | 495 | 197 |
5 | Gmelina melina | 4.408368 | -75.142898 | 937 | Cortolima | 2017-09-30 08:48:01 | 495 | 197 |
6 | Gmelina melina | 4.408599 | -75.142869 | 937 | Cortolima | 2017-09-30 08:44:46 | 495 | 197 |
7 | Gmelina melina | 4.408738 | -75.142816 | 937 | Cortolima | 2017-09-30 08:41:28 | 495 | 197 |
8 | Gmelina melina | 4.408872 | -75.14284 | 937 | Cortolima | 2017-09-30 08:37:49 | 495 | 197 |
9 | Gmelina melina | 4.409477 | -75.142604 | 934 | Cortolima | 2017-09-30 08:34:29 | 495 | 197 |
10 | Gmelina melina | 4.409829 | -75.142551 | 934 | Cortolima | 2017-09-30 08:30:29 | 495 | 197 |
11 | Gmelina melina | 4.410075 | -75.142449 | 934 | Cortolima | 2017-09-30 08:27:46 | 235 | 197 |
12 | Ocobo | 4.40978 | -75.146175 | 942 | Cortolima | 2017-09-30 07:50:09 | 427 | 399 |
13 | Ocobo | 4.409618 | -75.146547 | 942 | Cortolima | 2017-09-30 07:44:29 | 427 | 399 |
14 | Tulipan africano | 4.409752 | -75.146766 | 942 | Cortolima | 2017-09-30 07:41:22 | 427 | 387 |
15 | Ocobo | 4.409678 | -75.146869 | 942 | Cortolima | 2017-09-30 07:37:38 | 427 | 399 |
16 | Tulipan africano | 4.409698 | -75.146806 | 942 | Cortolima | 2017-09-30 07:34:29 | 427 | 387 |
17 | Ocobo | 4.409741 | -75.146846 | 942 | Cortolima | 2017-09-30 07:33:30 | 21 | 399 |
18 | Ocobo | 4.409816 | -75.146937 | 942 | Cortolima | 2017-09-30 07:21:44 | 427 | 399 |
19 | Ocobo | 4.409771 | -75.146972 | 944 | Cortolima | 2017-09-30 07:18:31 | 427 | 399 |
20 | Ocobo | 4.409723 | -75.146991 | 944 | Cortolima | 2017-09-30 07:15:34 | 427 | 399 |
21 | Caucho matapalo | 4.409549 | -75.147259 | 944 | Cortolima | 2017-09-30 07:06:41 | 427 | 181 |
22 | Matarraton | 4.409442 | -75.147316 | 946 | Cortolima | 2017-09-30 07:01:23 | 427 | 196 |
23 | Limon | 4.407188 | -75.145363 | 945 | Cortolima | 2017-09-29 13:18:53 | 427 | 108 |
24 | Tulipan africano | 4.407031 | -75.145365 | 945 | Cortolima | 2017-09-29 13:16:25 | 427 | 387 |
25 | Tulipan africano | 4.406994 | -75.145446 | 945 | Cortolima | 2017-09-29 13:14:21 | 427 | 387 |
26 | Almendro | 4.407007 | -75.145545 | 945 | Cortolima | 2017-09-29 13:10:58 | 427 | 408 |
27 | Tulipan africano | 4.407058 | -75.145604 | 945 | Cortolima | 2017-09-29 13:08:34 | 427 | 387 |
28 | Tulipan africano | 4.407313 | -75.145532 | 945 | Cortolima | 2017-09-29 13:05:58 | 427 | 387 |
29 | Millon croto | 4.407419 | -75.145919 | 945 | Cortolima | 2017-09-29 13:03:06 | 427 | 333 |
30 | Payande | 4.408384 | -75.145836 | 942 | Cortolima | 2017-09-29 12:56:04 | 427 | 321 |
31 | Palo cruz | 4.408325 | -75.145873 | 942 | Cortolima | 2017-09-29 12:52:44 | 427 | 52 |
32 | Carbonero | 4.408285 | -75.1459 | 942 | Cortolima | 2017-09-29 12:50:06 | 427 | 72 |
33 | Ocobo | 4.408301 | -75.145927 | 942 | Cortolima | 2017-09-29 12:47:46 | 427 | 399 |
34 | Habano laurel de judea | 4.408241 | -75.146456 | 946 | Cortolima | 2017-09-29 12:41:37 | 427 | 286 |
35 | Guanabano | 4.40834 | -75.146499 | 946 | Cortolima | 2017-09-29 12:39:05 | 427 | 27 |
36 | Limon | 4.407994 | -75.146565 | 946 | Cortolima | 2017-09-29 11:33:54 | 427 | 108 |
37 | Ocobo | 4.408027 | -75.146479 | 946 | Cortolima | 2017-09-29 11:30:12 | 427 | 399 |
38 | Ocobo | 4.408137 | -75.146461 | 946 | Cortolima | 2017-09-29 11:26:23 | 427 | 399 |
39 | Mirto | 4.408015 | -75.14638 | 946 | Cortolima | 2017-09-29 11:20:22 | 427 | 278 |
40 | Pera de malaca | 4.40797 | -75.146362 | 946 | Cortolima | 2017-09-29 11:17:23 | 427 | 396 |
41 | Cardo | 4.407872 | -75.146336 | 946 | Cortolima | 2017-09-29 11:15:07 | 427 | 96 |
42 | Nacedero | 4.407765 | -75.146281 | 947 | Cortolima | 2017-09-29 11:12:07 | 427 | 418 |
43 | Nevado | 4.407752 | -75.146286 | 947 | Cortolima | 2017-09-29 11:09:31 | 427 | 217 |
44 | Pino libro | 4.407647 | -75.146236 | 947 | Cortolima | 2017-09-29 10:01:47 | 427 | 323 |
45 | Pera de malaca | 4.407688 | -75.146496 | 947 | Cortolima | 2017-09-29 09:56:04 | 427 | 396 |
46 | Nevado | 4.407729 | -75.146516 | 947 | Cortolima | 2017-09-29 09:53:02 | 427 | 217 |
47 | Mirto | 4.407751 | -75.146528 | 947 | Cortolima | 2017-09-29 09:49:21 | 427 | 278 |
48 | Monaca | 4.407789 | -75.146539 | 947 | Cortolima | 2017-09-29 09:45:46 | 427 | 55 |
49 | Ebano arboreo costenno | 4.407853 | -75.146571 | 947 | Cortolima | 2017-09-29 09:42:11 | 427 | 62 |
50 | Arbol de la felicidad | 4.407981 | -75.146618 | 946 | Cortolima | 2017-09-29 09:39:15 | 427 | 149 |
51 | Araza | 4.408025 | -75.146794 | 946 | Cortolima | 2017-09-29 09:34:29 | 427 | 171 |
52 | Limon | 4.407855 | -75.147262 | 948 | Cortolima | 2017-09-29 09:23:28 | 427 | 108 |
53 | Acacio amarillo | 4.407808 | -75.14722 | 948 | Cortolima | 2017-09-29 09:21:11 | 427 | 376 |
54 | Casco de vaca pate buey | 4.40783 | -75.147228 | 948 | Cortolima | 2017-09-29 09:18:27 | 427 | 44 |
55 | Saman | 4.40787 | -75.147281 | 948 | Cortolima | 2017-09-29 09:14:29 | 427 | 359 |
56 | Noni | 4.407819 | -75.1474 | 948 | Cortolima | 2017-09-29 09:11:40 | 427 | 273 |
57 | Ocobo | 4.407884 | -75.147416 | 948 | Cortolima | 2017-09-29 09:08:25 | 427 | 399 |
58 | Ocobo | 4.407956 | -75.147456 | 948 | Cortolima | 2017-09-29 09:05:49 | 427 | 399 |
59 | Ocobo | 4.407999 | -75.147477 | 948 | Cortolima | 2017-09-29 09:02:34 | 427 | 399 |
60 | Noni | 4.408017 | -75.147453 | 948 | Cortolima | 2017-09-29 08:59:39 | 427 | 273 |
61 | Saman | 4.408031 | -75.147496 | 948 | Cortolima | 2017-09-29 08:53:50 | 427 | 359 |
62 | Limon | 4.408128 | -75.147509 | 948 | Cortolima | 2017-09-29 08:40:49 | 427 | 108 |
63 | Mango | 4.408165 | -75.147531 | 948 | Cortolima | 2017-09-29 08:37:44 | 427 | 261 |
64 | Almendro | 4.408224 | -75.147574 | 948 | Cortolima | 2017-09-29 08:35:05 | 427 | 408 |
65 | Saman | 4.408299 | -75.147641 | 948 | Cortolima | 2017-09-29 08:30:44 | 427 | 359 |
66 | Saman | 4.408409 | -75.147732 | 948 | Cortolima | 2017-09-29 08:28:25 | 427 | 359 |
67 | Gualanday | 4.408259 | -75.147906 | 949 | Cortolima | 2017-09-29 08:24:25 | 427 | 227 |
68 | Chirlobirlo | 4.408155 | -75.147879 | 949 | Cortolima | 2017-09-29 08:21:41 | 427 | 405 |
69 | Saman | 4.408184 | -75.147984 | 949 | Cortolima | 2017-09-29 08:17:47 | 427 | 359 |
70 | Acacio rojo | 4.408012 | -75.14785 | 949 | Cortolima | 2017-09-29 08:12:12 | 427 | 146 |
71 | Ocobo | 4.408036 | -75.147905 | 949 | Cortolima | 2017-09-29 08:09:40 | 427 | 399 |
72 | Palma areca | 4.407845 | -75.147289 | 948 | Cortolima | 2017-09-29 08:04:44 | 427 | 153 |
73 | Noni | 4.408124 | -75.147205 | 948 | Cortolima | 2017-09-29 08:01:15 | 427 | 273 |
74 | Pera de malaca | 4.408183 | -75.147225 | 948 | Cortolima | 2017-09-29 07:58:27 | 427 | 396 |
75 | Totumo | 4.408358 | -75.147288 | 948 | Cortolima | 2017-09-29 07:55:52 | 427 | 136 |
76 | Ocobo | 4.408551 | -75.147219 | 948 | Cortolima | 2017-09-29 07:48:33 | 427 | 399 |
77 | Ocobo | 4.408567 | -75.147229 | 948 | Cortolima | 2017-09-29 07:41:55 | 427 | 399 |
78 | Arbol de la felicidad | 4.408503 | -75.14732 | 948 | Cortolima | 2017-09-29 07:34:40 | 427 | 149 |
79 | Chirlobirlo | 4.408503 | -75.147339 | 948 | Cortolima | 2017-09-29 07:31:31 | 427 | 405 |
80 | Ocobo | 4.408476 | -75.147379 | 948 | Cortolima | 2017-09-29 07:28:12 | 427 | 399 |
81 | Papayuelo espinaco | 4.408454 | -75.147449 | 948 | Cortolima | 2017-09-29 07:24:25 | 427 | 120 |
82 | Palma areca | 4.408435 | -75.147512 | 948 | Cortolima | 2017-09-29 07:20:20 | 427 | 153 |
83 | Igua | 4.408478 | -75.14757 | 948 | Cortolima | 2017-09-29 07:16:45 | 427 | 343 |
84 | Payande | 4.408665 | -75.147685 | 946 | Cortolima | 2017-09-29 07:08:22 | 427 | 321 |
85 | Limon | 4.406684 | -75.146053 | 945 | Cortolima | 2017-09-27 12:05:34 | 256 | 108 |
86 | Aguacate | 4.407421 | -75.147058 | 948 | Cortolima | 2017-09-27 11:55:24 | 256 | 306 |
87 | Aguacate | 4.407022 | -75.146159 | 949 | Cortolima | 2017-09-27 11:51:36 | 256 | 306 |
88 | Cobalonga | 4.406942 | -75.14599 | 945 | Cortolima | 2017-09-27 11:47:01 | 256 | 413 |
89 | Almendro | 4.407037 | -75.1472 | 951 | Cortolima | 2017-09-27 10:37:39 | 256 | 408 |
90 | Oiti | 4.407147 | -75.147299 | 948 | Cortolima | 2017-09-27 10:33:34 | 256 | 247 |
91 | Oiti | 4.407133 | -75.147267 | 948 | Cortolima | 2017-09-27 10:31:11 | 256 | 247 |
92 | Tulipan africano | 4.407332 | -75.147204 | 948 | Cortolima | 2017-09-27 10:27:20 | 256 | 387 |
93 | Pera de malaca | 4.407274 | -75.147207 | 948 | Cortolima | 2017-09-27 10:24:31 | 256 | 396 |
94 | Marannon | 4.407496 | -75.147741 | 948 | Cortolima | 2017-09-27 10:20:51 | 256 | 24 |
95 | Oiti | 4.407506 | -75.147782 | 951 | Cortolima | 2017-09-27 10:16:34 | 256 | 247 |
96 | Munneco | 4.407581 | -75.147965 | 951 | Cortolima | 2017-09-27 10:13:50 | 256 | 130 |
97 | Pino libro | 4.407626 | -75.148101 | 951 | Cortolima | 2017-09-27 10:10:57 | 256 | 323 |
98 | Guanabano | 4.408489 | -75.145839 | 942 | Cortolima | 2017-09-29 12:54:09 | 427 | 27 |
99 | Pera de malaca | 4.408879 | -75.146185 | 944 | Cortolima | 2017-09-29 12:49:46 | 427 | 396 |
100 | Pera de malaca | 4.408696 | -75.146106 | 941 | Cortolima | 2017-09-29 12:46:29 | 427 | 396 |
End of preview.
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