This thesis describes the development of DataMole, a new tool written in Python, equipped with a Qt-based graphical interface, that can support researchers during data exploration and preprocessing activities. Data transformation pipelines can be defined and executed within a simple, user-friendly graphical environment, effectively providing an intuitive approach to data manipulation. The tool also embeds functionalities for data visualisation through interactive plots, like scatterplots and line charts, and provides a specific feature for the extraction of time series from longitudinal datasets

A graphical data analysis tool for dataset enhancement and preprocessing

Zangari, Alessandro
2020/2021

Abstract

This thesis describes the development of DataMole, a new tool written in Python, equipped with a Qt-based graphical interface, that can support researchers during data exploration and preprocessing activities. Data transformation pipelines can be defined and executed within a simple, user-friendly graphical environment, effectively providing an intuitive approach to data manipulation. The tool also embeds functionalities for data visualisation through interactive plots, like scatterplots and line charts, and provides a specific feature for the extraction of time series from longitudinal datasets
2020-09-24
100
data preprocessing, interactive tool, data visualization, longitudinal dataset, machine learning
File in questo prodotto:
File Dimensione Formato  
tesi_Zangari.pdf.pdf

accesso aperto

Dimensione 3.84 MB
Formato Adobe PDF
3.84 MB Adobe PDF Visualizza/Apri

The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/22412