| Name | tsum JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | None |
| Summary | Summarize data in Dask DataFrames. |
| upload_time | 2024-04-07 06:09:21 |
| maintainer | None |
| docs_url | None |
| author | Fasih Khatib |
| requires_python | <4.0,>=3.9 |
| license | None |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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## TSum - Table Summarization
> Given a table where rows correspond to records and columns correspond to attributes, we want to find a small number of patterns that succinctly summarize the dataset.
TSum is a [table summarization algorithm published by Google Research.](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/41683.pdf) This is a Python implementation of the algorithm using Dask Dataframes for scale.
### Usage
```python
import dask.dataframe as dd
from tsum import summarize, Pattern
from dask.distributed import LocalCluster
cluster = LocalCluster(n_workers=1, nthreads=8, diagnostics_port=8787)
client = cluster.get_client()
ddf: dd.DataFrame = ...
patterns: list[Pattern] = summarize(ddf=ddf)
```
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