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A profiling tool for tabular data leveraging the powerful capabilities of LLMs, appropriate for data scientists.

Project description

TableSage

A profiling tool for tabular data leveraging the powerful capabilities of LLMs, appropriate for data scientists.

Features

Table-related features Attribute-related features

  • Table-related features: Table-related features of TableSage.
  • Table-related features: Attribute-related features of TableSage. Dashed lines indicate optional arguments, but at least one should be provided.
Feature Sub-Feature Input Output
Table Table Summarization Table Property
Table Type Annotation Table Property
Column Column Summarization Table Property
Column Type Annotation Table Property
Extraction Insights Extraction List of Official Properties (Optional)
List of Generated Properties (Optional)
(At least one)
List of Insights
Spatial Information Extraction Table Description Property
Temporal Information Extraction Table Description Property
Comparison Properties Comparison List of Official Properties
List of Generated Properties
List of Comparisons
Fusion Alternative Properties Fusion List of Official Properties (Optional)
List of Generated Properties (Optional)
List of Insights (Optional)
(At least one)
Property
Complementary Properties Merging List of Official Properties (Optional)
List of Generated Properties (Optional)
(At least one)
Property

Quickstart

Installation

pip install tablesage

Usage

You can easily use TableSage by:

from tablesage import TableSage

p = TableSage()
p.load_dataset(path=<path>, separator=<separator>)
profile = p.profile_dataset(<model>, endpoint=<openai-endpoint>, token=<token>)

You can find more information about OpenAI endpoints here.

Acknowledgements

This work was partially funded by the EU Horizon Europe projects STELAR (GA. 101070122)

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