Datasets:

waynehamadi2
/

datacircle

Error code:   FeaturesError
Exception:    ArrowTypeError
Message:      ("Expected bytes, got a 'float' object", 'Conversion failed for column resultsCap with type object')
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4645, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2866, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3073, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2581, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 199, in _generate_tables
                  pa_table = pa.Table.from_pandas(df)
                File "pyarrow/table.pxi", line 4768, in pyarrow.lib.Table.from_pandas
                File "/usr/local/lib/python3.14/site-packages/pyarrow/pandas_compat.py", line 664, in dataframe_to_arrays
                  arrays[i] = maybe_fut.result()
                              ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/concurrent/futures/_base.py", line 443, in result
                  return self.__get_result()
                         ~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/concurrent/futures/_base.py", line 395, in __get_result
                  raise self._exception
                File "/usr/local/lib/python3.14/concurrent/futures/thread.py", line 86, in run
                  result = ctx.run(self.task)
                File "/usr/local/lib/python3.14/concurrent/futures/thread.py", line 73, in run
                  return fn(*args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/pyarrow/pandas_compat.py", line 639, in convert_column
                  raise e
                File "/usr/local/lib/python3.14/site-packages/pyarrow/pandas_compat.py", line 633, in convert_column
                  result = pa.array(col, type=type_, from_pandas=True, safe=safe)
                File "pyarrow/array.pxi", line 390, in pyarrow.lib.array
                File "pyarrow/array.pxi", line 91, in pyarrow.lib._ndarray_to_array
                  check_status(NdarrayToArrow(pool, values, mask, from_pandas,
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowTypeError: ("Expected bytes, got a 'float' object", 'Conversion failed for column resultsCap with type object')

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Datacircle

Datacircle lists all the GTM APIs.

Every GTM API we find, one row for each plan of each call: what it costs per 1,000, what it charges when it finds nothing, its rate limits, its speed and the fields it returns.

Buyers compare plans on the sheet. Each API plan on the sheet links to its own page, with an llms.txt for AI agents. Each plan's page links to the provider's site and API docs.

Anyone can download the sheet as CSV, JSON or a zip, with no sign-up. The CSV lists the pages we read each row from.

Download every GTM API plan on Datacircle as one file, with a skill that tells your AI how to query it: datacircle.dev/SKILL.md.

Website: https://datacircle.dev
The file: https://datacircle.dev/datacircle.json and https://datacircle.dev/datacircle.csv
Fields: https://datacircle.dev/fields
Skill: https://datacircle.dev/SKILL.md
Docs: https://datacircle.dev/docs
Licence: CC BY 4.0

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