Datasets:
File size: 4,057 Bytes
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task_categories:
- time-series-forecasting
tags:
- tsfile
- timeseries
- time-series
- format:tsfile
pretty_name: knowable
configs:
- config_name: default
data_files:
- split: train
path: congress_trades_2.tsfile
- split: train
path: congress_trades_3.tsfile
- split: train
path: congress_trades_4.tsfile
- split: train
path: congress_trades_5.tsfile
- split: train
path: congress_trades_6.tsfile
- split: train
path: congress_trades_7.tsfile
- split: train
path: congress_trades_8.tsfile
- split: train
path: house_filings_1.tsfile
- split: train
path: house_filings_2.tsfile
- split: train
path: house_filings_4.tsfile
- split: train
path: house_filings_5.tsfile
- split: train
path: house_filings_6.tsfile
- split: train
path: house_filings_8.tsfile
- split: train
path: house_filings_9.tsfile
- split: train
path: insider_transactions_2.tsfile
- split: train
path: insider_transactions_3.tsfile
- split: train
path: insider_transactions_5.tsfile
- split: train
path: insider_transactions_6.tsfile
- split: train
path: insider_transactions_7.tsfile
- split: train
path: insider_transactions_8.tsfile
- split: train
path: insider_transactions_9.tsfile
- split: train
path: senate_filings_1.tsfile
- split: train
path: senate_filings_2.tsfile
- split: train
path: senate_filings_3.tsfile
- split: train
path: senate_filings_4.tsfile
- split: train
path: senate_filings_5.tsfile
- split: train
path: senate_filings_6.tsfile
- split: train
path: senate_filings_7.tsfile
- split: train
path: senate_filings_8.tsfile
- split: train
path: senate_filings_9.tsfile
---
# knowable (TsFile)
Apache TsFile version of [`jwlutz/knowable`](https://huggingface.co/datasets/jwlutz/knowable).
- **Converted rows:** 2,986,261
- **Data files:** `['congress_trades_2.tsfile', 'congress_trades_3.tsfile', 'congress_trades_4.tsfile', 'congress_trades_5.tsfile', 'congress_trades_6.tsfile', 'congress_trades_7.tsfile', 'congress_trades_8.tsfile', 'house_filings_1.tsfile', 'house_filings_2.tsfile', 'house_filings_4.tsfile', 'house_filings_5.tsfile', 'house_filings_6.tsfile', 'house_filings_8.tsfile', 'house_filings_9.tsfile', 'insider_transactions_2.tsfile', 'insider_transactions_3.tsfile', 'insider_transactions_5.tsfile', 'insider_transactions_6.tsfile', 'insider_transactions_7.tsfile', 'insider_transactions_8.tsfile', 'insider_transactions_9.tsfile', 'senate_filings_1.tsfile', 'senate_filings_2.tsfile', 'senate_filings_3.tsfile', 'senate_filings_4.tsfile', 'senate_filings_5.tsfile', 'senate_filings_6.tsfile', 'senate_filings_7.tsfile', 'senate_filings_8.tsfile', 'senate_filings_9.tsfile']`
The `fund_holdings` table (~890 MB per daily release) is not included; converted tables are congress_trades, insider_transactions, house_filings and senate_filings. Overlapping daily releases are deduplicated.
## Usage
Install the Apache TsFile Python SDK (`pip install tsfile`) and read a converted file:
```python
from pathlib import Path
from tsfile import TsFileReader
path = Path("congress_trades_2.tsfile")
with TsFileReader(str(path)) as reader:
schemas = reader.get_all_table_schemas()
print("tables:", list(schemas))
table_name = next(iter(schemas))
table = schemas[table_name]
columns = [column.get_column_name() for column in table.get_columns()]
print("columns:", columns)
field_names = [
column.get_column_name()
for column in table.get_columns()
if column.get_column_name() not in {"Time", "time"}
]
if field_names:
with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
```
## Source & license
- Original dataset: https://huggingface.co/datasets/jwlutz/knowable
- License: not declared by the original dataset; please defer to the original.
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