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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 3 new columns ({'End_Pointer', 'Avg_Dist', 'Spearman'}) and 6 missing columns ({'Fill', 'Mean', 'Max', 'Cidx', 'Rec', 'Min'}).
This happened while the csv dataset builder was generating data using
hf://datasets/SA61team5/ultrasonic-waste-bin-sensor-raw/Container_1000_recs_Corrected_with_metrics.csv (at revision 445111ca97275e0afb71fcf2ea6b9e593068e937)
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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
Date: string
End_Pointer: int64
Avg_Dist: double
Spearman: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 722
to
{'Date': Value('string'), 'Fill': Value('int64'), 'Rec': Value('int64'), 'Cidx': Value('float64'), 'Max': Value('float64'), 'Min': Value('float64'), 'Mean': Value('float64')}
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 1339, 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 972, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, 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 3 new columns ({'End_Pointer', 'Avg_Dist', 'Spearman'}) and 6 missing columns ({'Fill', 'Mean', 'Max', 'Cidx', 'Rec', 'Min'}).
This happened while the csv dataset builder was generating data using
hf://datasets/SA61team5/ultrasonic-waste-bin-sensor-raw/Container_1000_recs_Corrected_with_metrics.csv (at revision 445111ca97275e0afb71fcf2ea6b9e593068e937)
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.
Date string | Fill int64 | Rec int64 | Cidx float64 | Max float64 | Min float64 | Mean float64 |
|---|---|---|---|---|---|---|
2021-01-09 12:39:00 | 0 | 0 | null | null | null | null |
2021-01-16 11:30:00 | 100 | 1 | 0 | 100 | 5 | 52.5 |
2021-01-16 12:28:00 | 40 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-16 13:28:00 | 40 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-17 12:34:00 | 40 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-18 12:41:00 | 40 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-19 12:48:00 | 40 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-20 12:55:00 | 40 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-20 18:27:00 | 100 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-21 13:02:00 | 100 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-22 13:07:00 | 100 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-23 13:12:00 | 100 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-24 13:17:00 | 100 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-26 13:28:00 | 100 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-27 13:34:00 | 100 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-28 13:39:00 | 100 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-29 11:45:00 | 44 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-29 13:46:00 | 44 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-29 18:48:00 | 40 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-29 23:49:00 | 56 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-30 12:53:00 | 5 | 0 | 0 | 100 | 5 | 52.5 |
2021-01-30 13:23:00 | 58 | 0 | 0 | 100 | 39 | 69.5 |
2021-01-30 13:54:00 | 44 | 0 | 0 | 100 | 39 | 69.5 |
2021-01-30 15:25:00 | 79 | 0 | 0 | 100 | 39 | 69.5 |
2021-01-31 12:00:00 | 39 | 0 | 0 | 100 | 39 | 69.5 |
2021-01-31 12:31:00 | 66 | 0 | 0 | 100 | 66 | 83 |
2021-01-31 14:02:00 | 66 | 0 | 0 | 100 | 66 | 83 |
2021-01-31 14:33:00 | 77 | 0 | 0 | 100 | 77 | 88.5 |
2021-02-01 14:08:00 | 77 | 0 | 0 | 100 | 77 | 88.5 |
2021-02-01 17:10:00 | 100 | 0 | 0 | 100 | 100 | 100 |
2021-02-01 20:11:00 | 0 | 1 | 2 | 0 | 0 | 0 |
2021-02-02 14:16:00 | 6 | 0 | 2 | 6 | 6 | 6 |
2021-02-03 07:20:00 | 35 | 0 | 2 | 35 | 6 | 20.5 |
2021-02-03 10:51:00 | 13 | 0 | 2 | 35 | 6 | 20.5 |
2021-02-03 12:22:00 | 28 | 0 | 2 | 35 | 6 | 20.5 |
2021-02-03 14:24:00 | 19 | 0 | 2 | 35 | 6 | 20.5 |
2021-02-03 14:55:00 | 28 | 0 | 2 | 35 | 6 | 20.5 |
2021-02-03 15:56:00 | 19 | 0 | 2 | 35 | 6 | 20.5 |
2021-02-03 16:26:00 | 27 | 0 | 2 | 35 | 6 | 20.5 |
2021-02-03 18:58:00 | 6 | 0 | 2 | 35 | 6 | 20.5 |
2021-02-03 19:28:00 | 27 | 0 | 2 | 35 | 18 | 26.5 |
2021-02-03 19:59:00 | 44 | 0 | 2 | 44 | 18 | 31 |
2021-02-04 10:32:00 | 26 | 0 | 2 | 44 | 18 | 31 |
2021-02-04 12:03:00 | 18 | 0 | 2 | 44 | 18 | 31 |
2021-02-04 12:34:00 | 35 | 0 | 2 | 44 | 20 | 32 |
2021-02-04 13:05:00 | 20 | 0 | 2 | 44 | 20 | 32 |
2021-02-04 13:36:00 | 42 | 0 | 2 | 44 | 24 | 34 |
2021-02-04 14:37:00 | 24 | 0 | 2 | 44 | 24 | 34 |
2021-02-04 15:38:00 | 42 | 0 | 2 | 44 | 42 | 43 |
2021-02-05 14:43:00 | 44 | 0 | 2 | 44 | 44 | 44 |
2021-02-06 01:15:00 | 0 | 1 | 4 | 0 | 0 | 0 |
2021-02-06 14:48:00 | 0 | 0 | 4 | 0 | 0 | 0 |
2021-02-06 20:50:00 | 26 | 0 | 4 | 26 | 13 | 19.5 |
2021-02-07 09:53:00 | 18 | 0 | 4 | 26 | 13 | 19.5 |
2021-02-07 11:54:00 | 28 | 0 | 4 | 28 | 13 | 20.5 |
2021-02-07 14:55:00 | 28 | 0 | 4 | 28 | 13 | 20.5 |
2021-02-07 17:26:00 | 17 | 0 | 4 | 28 | 13 | 20.5 |
2021-02-07 17:57:00 | 31 | 0 | 4 | 31 | 13 | 22 |
2021-02-08 04:00:00 | 19 | 0 | 4 | 31 | 13 | 22 |
2021-02-08 07:01:00 | 27 | 0 | 4 | 31 | 13 | 22 |
2021-02-08 12:03:00 | 18 | 0 | 4 | 31 | 13 | 22 |
2021-02-08 12:34:00 | 30 | 0 | 4 | 31 | 13 | 22 |
2021-02-08 15:05:00 | 30 | 0 | 4 | 31 | 13 | 22 |
2021-02-08 17:06:00 | 43 | 0 | 4 | 43 | 13 | 28 |
2021-02-08 18:07:00 | 25 | 0 | 4 | 43 | 13 | 28 |
2021-02-09 15:12:00 | 40 | 0 | 4 | 43 | 13 | 28 |
2021-02-09 21:14:00 | 13 | 0 | 4 | 43 | 13 | 28 |
2021-02-09 22:15:00 | 40 | 0 | 4 | 43 | 17 | 30 |
2021-02-10 15:19:00 | 40 | 0 | 4 | 43 | 17 | 30 |
2021-02-10 21:21:00 | 55 | 0 | 4 | 55 | 17 | 36 |
2021-02-11 05:53:00 | 38 | 0 | 4 | 55 | 17 | 36 |
2021-02-11 08:25:00 | 47 | 0 | 4 | 55 | 17 | 36 |
2021-02-11 15:27:00 | 55 | 0 | 4 | 55 | 17 | 36 |
2021-02-12 13:33:00 | 17 | 0 | 4 | 55 | 17 | 36 |
2021-02-12 14:04:00 | 71 | 0 | 4 | 71 | 28 | 49.5 |
2021-02-12 15:35:00 | 71 | 0 | 4 | 71 | 28 | 49.5 |
2021-02-12 16:06:00 | 28 | 0 | 4 | 71 | 28 | 49.5 |
2021-02-12 17:37:00 | 64 | 0 | 4 | 71 | 64 | 67.5 |
2021-02-12 22:09:00 | 72 | 0 | 4 | 72 | 72 | 72 |
2021-02-12 23:10:00 | 0 | 1 | 5 | 0 | 0 | 0 |
2021-02-13 11:12:00 | 27 | 0 | 5 | 27 | 6 | 16.5 |
2021-02-13 11:43:00 | 16 | 0 | 5 | 27 | 6 | 16.5 |
2021-02-13 15:45:00 | 16 | 0 | 5 | 27 | 6 | 16.5 |
2021-02-13 16:46:00 | 26 | 0 | 5 | 27 | 6 | 16.5 |
2021-02-13 18:48:00 | 10 | 0 | 5 | 27 | 6 | 16.5 |
2021-02-13 19:18:00 | 25 | 0 | 5 | 27 | 6 | 16.5 |
2021-02-13 20:49:00 | 11 | 0 | 5 | 27 | 6 | 16.5 |
2021-02-14 03:21:00 | 22 | 0 | 5 | 27 | 6 | 16.5 |
2021-02-14 15:24:00 | 6 | 0 | 5 | 27 | 6 | 16.5 |
2021-02-14 15:55:00 | 26 | 0 | 5 | 27 | 24 | 25.5 |
2021-02-14 17:57:00 | 44 | 0 | 5 | 44 | 24 | 34 |
2021-02-14 19:58:00 | 24 | 0 | 5 | 44 | 24 | 34 |
2021-02-15 16:02:00 | 40 | 0 | 5 | 44 | 40 | 42 |
2021-02-16 15:08:00 | 72 | 0 | 5 | 72 | 42 | 57 |
2021-02-16 16:09:00 | 43 | 0 | 5 | 72 | 42 | 57 |
2021-02-16 16:40:00 | 72 | 0 | 5 | 72 | 42 | 57 |
2021-02-17 09:44:00 | 42 | 0 | 5 | 72 | 42 | 57 |
2021-02-17 16:17:00 | 42 | 0 | 5 | 72 | 42 | 57 |
2021-02-18 10:53:00 | 80 | 0 | 5 | 80 | 43 | 61.5 |
2021-02-18 16:26:00 | 43 | 0 | 5 | 80 | 43 | 61.5 |
End of preview.
YAML Metadata Warning: empty or missing yaml metadata in repo card
Check out the documentation for more information.
Directory Structure
The directory is structured in the following way:
The file "ids.csv" is just one table line entry that has the ids of all the containters present in the dataset. Use this file has a helper to iterate over the dictionary.
The file "INFO.csv" has relevant data about the containers; namely "Capacity"; "WasteType"; "Latitude" and "Longitude".
Then, for each container; there are four files that have the following naming:
- Container_IDrecs_UnCorrected_with_metrics.csv
- Container_IDfill_UnCorrected_with_metrics.csv
- Container_IDrecs_Corrected_with_metrics.csv
- Container_IDfill_Corrected_with_metrics.csv
The fill files have the information about the Fill level of the Container. Aditional columns are the Max and Min monotonic aproximations between each collection; along with their mean (middle point) value; The "REC" is a mask set to true for the first fill value measured after a collection is made; the "Cidx" wich is a unique indentifier for each fill value between each collection which allows to call groupby on each event. The first Date columns is for when the collections happenned.
The rec files have the information about the Collections made to that container. Aditional columns are the End_Pointer which is the row index for when that collection is made; along with AVG_DIST which is 100 minus the average difference between the Max and Min approximation until the next collection. And "Spearman which each the spearman coefficient for the fill values until the next collection scalled by 100.
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