Datasets:

smilegeng
/

bitcoin_price_timeseries

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
                  scan = self._scan_metadata(all_files)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 304, in _scan_metadata
                  from tsfile.constants import TIME_COLUMN, ColumnCategory
              ModuleNotFoundError: No module named 'tsfile'
              
              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/split_names.py", line 66, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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Bitcoin Price Time Series — 1-minute OHLCV (TsFile)

This dataset is a lossless conversion to the Apache TsFile format of the HuggingFace dataset Farmaanaa/bitcoin_price_timeseries: minute-by-minute Bitcoin price and volume data.

Original dataset

Source dataset: Farmaanaa/bitcoin_price_timeseries
Preparation: data cleaned and prepared by farmaanaa.ir
License: CC-BY-4.0
Content: minute-by-minute Open / High / Low / Close / Volume for Bitcoin (BTC).

Scale

1,048,575 one-minute records, 6 source columns
Time range: 2022-09-15 16:26 → 2024-09-13 04:00 (≈ 2 years, minute cadence)
Single asset (BTC) → a single time series, no TAG / device dimension

TsFile storage mapping (table model)

Role	Column	Type	Description
Time	source `Timestamp`	INT64 (ms)	Per-minute UTC timestamp, used as the time primary key
FIELD	`Open`	DOUBLE	Price at the start of the minute
FIELD	`High`	DOUBLE	Highest price during the minute
FIELD	`Low`	DOUBLE	Lowest price during the minute
FIELD	`Close`	DOUBLE	Price at the end of the minute
FIELD	`Volume`	DOUBLE	Total traded volume during the minute

Conversion notes

No TAG: a single BTC series; all OHLCV columns are FIELD.
Time: the source Timestamp column ("M/D/YYYY H:MM", minute cadence, stored in descending order in the CSV) is parsed to INT64 epoch milliseconds and the rows are sorted ascending by time (TsFile requires monotonically increasing time within a device). The original Timestamp text column is dropped; its information is preserved losslessly in Time.
OHLC kept as DOUBLE: Open/High are already fractional; Low/Close happen to be integer-valued in this CSV but are prices, so all four are unified to DOUBLE for type consistency. Volume is DOUBLE.
No rows dropped; timestamps are unique (no duplicates).
Gaps: about 440 minutes are absent across the 2-year span (exchange no-trade / downtime gaps in the source). This is a property of the source data — TsFile simply stores the points that exist; nothing was removed during conversion.

Layout

data/
└── bitcoin_price_timeseries.tsfile

The tool shards output every 2²⁰ = 1,048,576 rows; this dataset has 1,048,575 rows (one below the threshold), so it is a single .tsfile.

Usage

from tsfile import TsFileReader

reader = TsFileReader("data/bitcoin_price_timeseries.tsfile")
schemas = reader.get_all_table_schemas()
tname = next(iter(schemas))

cols = ["Open", "High", "Low", "Close", "Volume"]
with reader.query_table(tname, cols, batch_size=65536) as rs:
    while (batch := rs.read_arrow_batch()) is not None:
        df = batch.to_pandas()
        # ... process ...
reader.close()

Citation

@dataset{bitcoin_price_timeseries,
  title     = {Bitcoin Price Time Series Data},
  author    = {farmaanaa},
  year      = {2025},
  url        = {https://huggingface.co/datasets/Farmaanaa/bitcoin_price_timeseries},
  publisher = {Hugging Face}
}

Original dataset licensed under CC-BY-4.0.

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