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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: Failed to parse string: 'Chick-fil-A — Fairfax, VA' as a scalar of type double
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2143, in cast_array_to_feature
return array_cast(
array,
...<2 lines>...
allow_decimal_to_str=allow_decimal_to_str,
)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2006, in array_cast
return array.cast(pa_type)
~~~~~~~~~~^^^^^^^^^
File "pyarrow/array.pxi", line 1147, in pyarrow.lib.Array.cast
File "/usr/local/lib/python3.14/site-packages/pyarrow/compute.py", line 412, in cast
return call_function("cast", [arr], options, memory_pool)
File "pyarrow/_compute.pyx", line 604, in pyarrow._compute.call_function
File "pyarrow/_compute.pyx", line 399, in pyarrow._compute.Function.call
result = GetResultValue(
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: Failed to parse string: 'Chick-fil-A — Fairfax, VA' as a scalar of type double
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
name null | lat float64 | lng float64 | state string |
|---|---|---|---|
null | 32.8357 | -116.9996 | CA |
null | 28.0987 | -81.9668 | FL |
null | 47.6188 | -122.3394 | WA |
null | 37.5276 | -121.9861 | CA |
null | 42.9182 | -112.4809 | ID |
null | 36.0461 | -115.0362 | NV |
null | 33.7377 | -116.7199 | CA |
null | 33.9326 | -117.5675 | CA |
null | 38.3101 | -122.2991 | CA |
null | 45.6536 | -122.467 | WA |
null | 43.5972 | -96.5662 | SD |
null | 34.1798 | -118.7664 | CA |
null | 41.32 | -73.8822 | NY |
null | 28.2562 | -80.7502 | FL |
null | 41.1004 | -112.0085 | UT |
null | 35.2088 | -80.8739 | NC |
null | 40.386 | -82.4771 | OH |
null | 29.8859 | -97.6778 | TX |
null | 32.1297 | -110.9024 | AZ |
null | 32.8767 | -79.7888 | SC |
null | 39.208 | -84.3746 | OH |
null | 45.655 | -100.5371 | SD |
null | 40.7858 | -72.9354 | NY |
null | 41.8556 | -72.1681 | CT |
null | 34.9252 | -117.9428 | CA |
null | 34.2746 | -119.2159 | CA |
null | 38.9342 | -77.3395 | VA |
null | 37.7494 | -121.4484 | CA |
null | 46.973 | -123.8237 | WA |
null | 29.1895 | -82.1513 | FL |
null | 35.3001 | -80.8469 | NC |
null | 32.6978 | -97.2539 | TX |
null | 39.4475 | -79.5371 | WV |
null | 33.0981 | -96.8789 | TX |
null | 37.5895 | -122.0279 | CA |
null | 40.0605 | -75.027 | PA |
null | 34.2082 | -118.2294 | CA |
null | 43.0881 | -89.3509 | WI |
null | 36.8111 | -76.1543 | VA |
null | 35.947 | -79.0615 | NC |
null | 39.2704 | -84.7962 | OH |
null | 39.2493 | -76.7046 | MD |
null | 33.6318 | -111.9632 | AZ |
null | 44.3323 | -85.214 | MI |
null | 41.5472 | -87.8963 | IL |
null | 45.1435 | -84.662 | MI |
null | 39.0523 | -85.2533 | IN |
null | 35.1498 | -84.8736 | TN |
null | 34.1854 | -118.537 | CA |
null | 43.4157 | -86.3766 | MI |
null | 40.1613 | -85.3626 | IN |
null | 32.7867 | -115.5754 | CA |
null | 31.7851 | -106.465 | TX |
null | 35.0575 | -106.5841 | NM |
null | 40.8099 | -73.9402 | NY |
null | 36.7408 | -119.7741 | CA |
null | 35.6002 | -82.5659 | NC |
null | 41.1272 | -80.6475 | OH |
null | 47.6393 | -122.0669 | WA |
null | 38.0052 | -78.4845 | VA |
null | 33.4955 | -112.261 | AZ |
null | 34.7878 | -86.581 | AL |
null | 40.6691 | -73.8789 | NY |
null | 40.8228 | -96.6734 | NE |
null | 33.4524 | -117.0953 | CA |
null | 47.1241 | -122.4394 | WA |
null | 39.2272 | -84.4517 | OH |
null | 41.3657 | -85.035 | IN |
null | 40.69 | -73.9998 | NY |
null | 47.2573 | -122.4935 | WA |
null | 40.8828 | -74.2469 | NJ |
null | 34.4391 | -119.8773 | CA |
null | 42.4331 | -83.0399 | MI |
null | 43.7096 | -116.6109 | ID |
null | 34.0467 | -117.2084 | CA |
null | 42.4834 | -71.8688 | MA |
null | 41.5434 | -87.4754 | IN |
null | 37.3267 | -121.7982 | CA |
null | 35.3849 | -82.5492 | NC |
null | 37.3717 | -122.0941 | CA |
null | 33.5902 | -112.1245 | AZ |
null | 40.5084 | -74.8287 | NJ |
null | 33.7133 | -118.0026 | CA |
null | 32.8281 | -79.8542 | SC |
null | 30.6449 | -97.8637 | TX |
null | 38.8785 | -104.699 | CO |
null | 29.6383 | -98.4338 | TX |
null | 29.3554 | -100.7935 | TX |
null | 45.1474 | -93.3507 | MN |
null | 33.7054 | -112.4127 | AZ |
null | 44.0576 | -95.1962 | MN |
null | 25.898 | -80.1836 | FL |
null | 44.2625 | -121.2024 | OR |
null | 35.1013 | -106.609 | NM |
null | 35.071 | -106.7062 | NM |
null | 29.5487 | -98.5989 | TX |
null | 35.6345 | -94.1696 | AR |
null | 40.9695 | -117.7346 | NV |
null | 39.1104 | -77.1669 | MD |
null | 34.1718 | -84.1286 | GA |
End of preview.
US Places: 130k+ Mapped Locations (18 categories)
Open datasets of mapped US places, extracted from OpenStreetMap and cleaned for analysis.
Each CSV: name, lat, lng, state.
Per-capita state rankings
Every category has all 50 US states ranked per 100k residents, with embeddable state maps: https://get-instamaps.com/rankings/pickleball-courts (swap the slug for any category above)
License & attribution
Data derived from OpenStreetMap, (c) OpenStreetMap contributors, licensed under the Open Database License (ODbL) 1.0. Cleaning/aggregation by InstaMaps. If you use these cuts, attribute both OpenStreetMap and link to the ranking page for the category you used.
Maintained by InstaMaps - turn any Google Sheet into a live map.
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