The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

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.