Excel Spreadsheet Analyzer
Amir Nassereldine, Patrick Chen, Jinjun Xiong

TL;DR
The paper introduces a tool that converts spreadsheets into an abstract intermediate representation to preserve cell dependencies, enabling seamless integration with Python for advanced data analysis.
Contribution
It presents a novel method for translating spreadsheets into an AIR that maintains cell dependencies, bridging the gap between spreadsheets and scientific programming languages.
Findings
Successfully preserves cell dependencies during conversion
Enables effective data analysis in Python using the library
Facilitates transition from spreadsheets to programming languages
Abstract
Spreadsheets are widely used in various fields to do large numerical analysis. While several companies have relied on spreadsheets for decades, data scientists are going in the direction of using scientific programming languages such as python to do their data analysis due to the support, community, and vast amount of libraries. While using python to analyze a company's spreadsheets, some information such as the formulas and dependencies of a cell are lost. We propose a tool that creates an abstract intermediate representation (AIR) of a spreadsheet. This representation facilitates the transfer from spreadsheets into scientific programming languages while preserving inter-dependency information about data. In addition to that, we build a python library on top of our tool to perform some data analysis in python.
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Taxonomy
TopicsTime Series Analysis and Forecasting · Spreadsheets and End-User Computing · Statistics Education and Methodologies
