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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 13 new columns ({'-69', '-46', '-47', '-30', '-91', '-73', '-83', '-59', '-79', '0.25', '-65', '-57', '1.25'}) and 13 missing columns ({'-61', '-54', '-95', '-51', '-66', '0', '-75', '-48', '-76', '-80', '1', '-53', '-32'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Brosnan/WIFI_RSSI_Indoor_Positioning_Dataset/Nexus4_Data/Long_Traj_Full.csv (at revision 48e546938ba5143a4af5c62ac868fa4d357b557b)

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 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              1.25: double
              0.25: double
              -30: int64
              -57: int64
              -47: int64
              -46: int64
              -69: int64
              -59: int64
              -65: int64
              -73: int64
              -79: int64
              -91: int64
              -83: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1613
              to
              {'1': Value(dtype='float64', id=None), '0': Value(dtype='float64', id=None), '-32': Value(dtype='int64', id=None), '-54': Value(dtype='int64', id=None), '-48': Value(dtype='int64', id=None), '-51': Value(dtype='int64', id=None), '-66': Value(dtype='int64', id=None), '-53': Value(dtype='int64', id=None), '-61': Value(dtype='int64', id=None), '-76': Value(dtype='int64', id=None), '-75': Value(dtype='int64', id=None), '-95': Value(dtype='int64', id=None), '-80': 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 1321, 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 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2013, 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 13 new columns ({'-69', '-46', '-47', '-30', '-91', '-73', '-83', '-59', '-79', '0.25', '-65', '-57', '1.25'}) and 13 missing columns ({'-61', '-54', '-95', '-51', '-66', '0', '-75', '-48', '-76', '-80', '1', '-53', '-32'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Brosnan/WIFI_RSSI_Indoor_Positioning_Dataset/Nexus4_Data/Long_Traj_Full.csv (at revision 48e546938ba5143a4af5c62ac868fa4d357b557b)
              
              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.

1
float64
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float64
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int64
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int64
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2.4087
0.011361
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3.9252
0.020731
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5.1841
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5.1962
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5.2009
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5.1705
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20.626
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20.679
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20.404
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20.5
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18.883
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17.379
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15.882
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-58
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14.37
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12.909
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11.363
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9.8655
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8.3643
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6.897
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5.2349
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5.2195
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5.2257
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-71
-71
-65
-94
End of preview.

WIFI RSSI Indoor Positioning Dataset

A reliable and comprehensive public WiFi fingerprinting database for researchers to implement and compare the indoor localization’s methods.The database contains RSSI information from 6 APs conducted in different days with the support of autonomous robot.

We use an autonomous robot to collect the WiFi fingerprint data. Our 3-wheel robot has multiple sensors including wheel odometer, an inertial measurement unit (IMU), a LIDAR, sonar sensors and a color and depth (RGB-D) camera. The robot can navigate to a target location to collect WiFi fingerprints automatically. The localization accuracy of the robot is 0.07 m ± 0.02 m. The dimension of the area is 21 m × 16 m. It has three long corridors. There are six APs and five of them provide two distinct MAC address for 2.4- and 5-GHz communications channels, respectively, except for one that only operates on 2.4-GHz frequency. There is one router can provide CSI information.

Data Format

X Position (m), Y Position (m), RSSI Feature 1 (dBm), RSSI Feature 2 (dBm), RSSI Feature 3 (dBm), RSSI Feature 4 (dBm), ...

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