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<p align="center"><img src="https://github.com/packing-box/python-dsff/raw/main/docs/pages/imgs/logo.png"></p> <h1 align="center">DataSet File Format <a href="https://twitter.com/intent/tweet?text=DataSet%20File%20Format%20-%20XSLX-based%20format%20for%20handling%20datasets.%0D%0ATiny%20library%20for%20handling%20a%20dataset%20as%20an%20XSLX%20and%20for%20converting%20it%20to%20ARFF,%20CSV%20or%20a%20FilelessDataset%20structure%20as%20for%20the%20Packing%20Box.%0D%0Ahttps%3a%2f%2fgithub%2ecom%2fpacking-box%2fpython-dsff%0D%0A&hashtags=python,dsff,machinelearning"><img src="https://img.shields.io/badge/Tweet--lightgrey?logo=twitter&style=social" alt="Tweet" height="20"/></a></h1> <h3 align="center">Store a dataset in XSLX-like format.</h3>

This library contains code for handling the DataSet File Format (DSFF) based on the XSLX format and for converting it to ARFF (for use with the Weka framework), CSV or a FilelessDataset structure (from the Packing Box).

pip install --user dsff

:sunglasses: Usage

Creating a DSFF from a FilelessDataset

>>> import dsff
>>> with dsff.DSFF() as f:
    f.write("/path/to/my-dataset")  # folder of a FilelessDataset (containing data.csv, features.json and metadata.json)
    f.to_arff()                     # creates ./my-dataset.arff
    f.to_csv()                      # creates ./my-dataset.csv
# while leaving the context, ./my-dataset.dsff is created

Creating a FilelessDataset from a DSFF

>>> import dsff
>>> with dsff.DSFF("/path/to/my-dataset.dsff") as f:
    f.to_dataset()  # creates ./[dsff-title] with data.csv, features.json and metadata.json

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