---
license: cc-by-4.0
annotations_creators:
- no-annotation
language_creators:
- found
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- time-series-forecasting
task_ids:
- univariate-time-series-forecasting
tags:
- time-series
- forecasting
- benchmark
- monash-time-series-forecasting-repository
- monash-tsf
- tsfile
- apache-tsfile
- modality:timeseries
- Time-series
- format:tsfile
pretty_name: bitcoin (TsFile format)
configs:
- config_name: default
  data_files:
  - split: train
    path: "*.tsfile"
---

# bitcoin (TsFile format)

18 daily time series including hash rate, block size, mining difficulty etc. as well as public opinion in the form of tweets and google searches mentioning the keyword bitcoin as potential influencer of the bitcoin price.

This repository contains the full source `.tsf` series from the Monash Time Series Forecasting Repository converted to [Apache TsFile](https://tsfile.apache.org/) format.

## Summary

- Source dataset: [`Monash-University/monash_tsf`](https://huggingface.co/datasets/Monash-University/monash_tsf)
- Original source: https://zenodo.org/record/5121965
- Monash subset: `bitcoin`
- Modalities: Time-series
- Source series: 18
- Rows: 82,458 flattened timestamped observations
- Frequency: `daily`
- Forecast horizon metadata: not specified
- Missing-values metadata: True
- Equal-length metadata: False
- Missing target values preserved as NaN: 8,088
- Series length range: 4,581 to 4,581
- TsFile output: 1 file (bitcoin.tsfile)

## Files

- `bitcoin.tsfile`

## TsFile Schema

| Column | Role | TsFile type |
|---|---|---|
| `Time` | TIME | INT64 |
| `series_id` | TAG | STRING |
| `series_name` | TAG | STRING |
| `start_timestamp` | TAG | STRING |
| `target` | FIELD | FLOAT |

## Conversion Notes

- Each source `.tsf` data row is stored as one TsFile device.
- Source `.tsf` attributes are stored as TAG columns.
- The `target` series values are flattened into timestamped rows and stored as a FLOAT FIELD.
- `Time` is synthesized from the source start timestamp and the `.tsf` frequency metadata, with millisecond precision.
- Large outputs may be sharded by the TsFile conversion tool; all listed shards belong to the same logical table `bitcoin`.

## Reading Example

```python
from tsfile import TsFileReader

reader = TsFileReader("bitcoin.tsfile")
schemas = reader.get_all_table_schemas()
```