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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'estandar' of the dataset.
Error code:   FeaturesError
Exception:    UnicodeDecodeError
Message:      'utf-8' codec can't decode byte 0xc8 in position 7: invalid continuation byte
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 4523, 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 2768, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2972, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2483, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 196, in _generate_tables
                  csv_file_reader = pd.read_csv(file, iterator=True, dtype=dtype, **self.config.pd_read_csv_kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
                  return function(*args, download_config=download_config, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1274, in xpandas_read_csv
                  return pd.read_csv(xopen(filepath_or_buffer, "rb", download_config=download_config), **kwargs)
                         ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1026, in read_csv
                  return _read(filepath_or_buffer, kwds)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 620, in _read
                  parser = TextFileReader(filepath_or_buffer, **kwds)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1620, in __init__
                  self._engine = self._make_engine(f, self.engine)
                                 ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1898, in _make_engine
                  return mapping[engine](f, **self.options)
                         ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 93, in __init__
                  self._reader = parsers.TextReader(src, **kwds)
                                 ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "pandas/_libs/parsers.pyx", line 574, in pandas._libs.parsers.TextReader.__cinit__
                File "pandas/_libs/parsers.pyx", line 663, in pandas._libs.parsers.TextReader._get_header
                File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
                File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
                File "pandas/_libs/parsers.pyx", line 2053, in pandas._libs.parsers.raise_parser_error
                File "<frozen codecs>", line 325, in decode
              UnicodeDecodeError: 'utf-8' codec can't decode byte 0xc8 in position 7: invalid continuation byte

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Peru SMV Financial Statements 2000-2026 (smv-eeff)

Normalized financial statements of 682 companies supervised by Peru's securities regulator (SMV), 2000-2026: balance sheet, income statement, cash flow, other comprehensive income and ratios. Six different charts of accounts (companies, banks, insurers, pension funds, brokers, CAVALI) are mapped to comparable concepts. Validated against the SMV's own index (208,788 comparisons, 5 source anomalies) and against statements published by the companies. Amounts are in thousands of the reporting currency (PEN or USD) and are not converted.

Estados financieros normalizados de 682 empresas supervisadas por la SMV del Perú, 2000-2026, con conceptos comparables entre planes de cuentas y ratios estándar.

Files

file content
resumen_anual.csv, resumen_trimestral.csv one row per company, period and type (individual or consolidated): key figures, standard concepts and ratios
estandar.parquet, ratios.parquet comparable concepts and ratios, long format
hechos_AAAA.parquet every reported account, one file per year (original SMV data, cleaned)
empresas.*, cuentas.csv, presentaciones.parquet catalogues and filing metadata
cambios_en_comparativos.parquet figures restated in the following year's statements
diccionario.md data dictionary (Spanish)

Quick use

from datasets import load_dataset
anual = load_dataset("AtlasLedger/smv-eeff", "resumen_anual", split="train").to_pandas()

Source, license and updates

Source: Superintendencia del Mercado de Valores (SMV), open data. License ODbL 1.0. Independent project, not affiliated with the SMV. The copy in this repository is refreshed by hand; the up-to-date version, code, methodology and monthly updates are at https://github.com/AtlasLedger/smv-eeff . Cite: https://doi.org/10.5281/zenodo.22981480

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