Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
sku: string
generated_at: timestamp[s]
tables: struct<gold_macro: struct<row_count: int64>>
child 0, gold_macro: struct<row_count: int64>
child 0, row_count: int64
totals: struct<row_count: int64, table_count: int64>
child 0, row_count: int64
child 1, table_count: int64
row_counts: struct<gold_macro: int64>
child 0, gold_macro: int64
files: list<item: string>
child 0, item: string
tier: string
to
{'sku': Value('string'), 'tier': Value('string'), 'generated_at': Value('timestamp[s]'), 'row_counts': {'gold_macro': Value('int64')}, 'files': List(Value('string'))}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_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 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
sku: string
generated_at: timestamp[s]
tables: struct<gold_macro: struct<row_count: int64>>
child 0, gold_macro: struct<row_count: int64>
child 0, row_count: int64
totals: struct<row_count: int64, table_count: int64>
child 0, row_count: int64
child 1, table_count: int64
row_counts: struct<gold_macro: int64>
child 0, gold_macro: int64
files: list<item: string>
child 0, item: string
tier: string
to
{'sku': Value('string'), 'tier': Value('string'), 'generated_at': Value('timestamp[s]'), 'row_counts': {'gold_macro': Value('int64')}, 'files': List(Value('string'))}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
AF-MACRO — sample package
License-clean African & emerging-markets company data — point-in-time, provenance-documented. See PROVENANCE.md and LICENSE.txt.
Quickstart
import duckdb, pandas as pd
df = duckdb.sql("select * from 'data/gold_fundamentals.parquet'").df() # or read_csv
df = pd.read_parquet('data/gold_fundamentals.parquet')
Excel: open any data/*.csv directly. Fields are documented in DICTIONARY.md; coverage and freshness in metrics.json.
This is a truncated free SAMPLE. Full history is in the paid tiers.
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