Home page

Introductive guide to coding, data cleaning and analysis for Python 3, with many worked exercises.

Nowadays, more and more decisions are taken upon factual and objective data. All disciplines, from engineering to social sciences, require to elaborate data and extract actionable information by analysing heterogeneous sources. This book of practical exercises gives an introduction to coding and data processing using Python, a programming language popular both in the industry and in research environments.

Intended audience

This book can be useful for both novices who never really programmed before, and for students with more technical background, who desire to know about data extraction, cleaning, analysis and visualization (among used frameworks there are Polars, Numpy and Jupyter). Data is going to be processed in a practical way, without delving into more advanced considerations about algorithmic complexity and data structures. To overcome issues and guarantee concrete didactical results, step-by-step tutorials are presented.

Acknowledments

SoftPython

Many of the tutorials presented here were adapted from the SoftPython guide.

Original author

David Leoni: Software engineer specialized in data integration and semantic web, has made applications in open data and medical in Italy and abroad. He frequently collaborates with University of Trento for teaching activities in various departments. Since 2019 is president of CoderDolomiti Association, where along with Marco Caresia manages volunteering movement CoderDojo Trento to teach creative coding to kids.

Email: david.leoni@unitn.it   Website: davidleoni.it

Contributors

Marco Caresia (2017 Autumn Edition assistant @DISI, University of Trento): He has been informatics teacher at Scuola Professionale Einaudi of Bolzano. He is president of the Trentino Alto Adige Südtirol delegatioon of the Associazione Italiana Formatori and vicepresident of CoderDolomiti Association.

Alessio Zamboni (2018 March Edition assistant @Sociology Department, University of Trento): Data scientist and software engineer with experience in NLP, GIS and knowledge management. Has collaborated to numerous research projects, collecting experiences in Europe and Asia. He strongly believes that ‘Programming is a work of art’.

Luca Bosotti (2020 Data Science Summerschool assistant, 2021 seminars @Sociology Department, University of Trento): Developer, scientist and professor. Believes the world is getting more and more complicated and interesting, so we must study it by taking advantage of all the available potential and reasoning. He thought to youngsters of all ages, from elementary schools up till university level and got impressed by the diversity of people who approach programming.

Massimiliano Luca (2019 summer edition teacher @Sociology Department, University of Trento): Loves learning new technilogies each day. Particularly interested in knowledge representation, data integration, data modeling and computational social science. Firmly believes it is vital to introduce youngsters to computer science, and has been mentoring at Coder Dojo DISI Master.

Others: We also wish to thank the students Ludovico Maria Valenti and Ioana Doleanu for the improvements to the numpy page, and Stefano Moro for the numerous reports.

License

The making of SoftPython was funded by Department of Information Engineering and Computer Science (DISI), University of Trento, and also Sociology and Mathematics departments.

Unless otherwise noted, the material in this website is original and distributed with license CC-BY 4.0 International Attribution https://creativecommons.org/licenses/by/4.0/deed.en. Basically, you can freely redistribute and modify the written content, just remember to cite University of Trento and the authors

Misc

All website pages are easily modifiable Jupyter notebooks, that were converted to web pages using Jupyter Book.