Python for non-computer scientists

Mirko Polato
Dipartimento di Matematica, Università degli Studi di Padova,


This course aims at providing skills, tools, and methodologies for manipulating and analyzing data using Python. First, the class will cover the basics of the Python programming language (i.e., built-in data types, basic expressions, control flow, functions) along with the environment used throughout the course (i.e., Google Colab/Jupyter Notebook). Afterward, students will explore a set of data science Python modules such as pandas (for data manipulation), numpy/scipy (for numerical and statistical computation), and matplotlib/seaborn/plotly (for data visualization). During the class, students will be challenged in solving problems on their own, using the acquired knowledge and exploiting the official documentation as well as established website/forums (e.g., StackOverflow). Eventually, at the end of this class, students will be able to autonomously use Python for performing data manipulation/analysis on their data.

- Introduction to the Python programming language, and Google Colab/Jupyter Notebook
- Python basics: built-in data types, basic expressions, control flow, and functions
- Installation and import of external modules, and how to use the official documentation
- Data manipulation with pandas
- Data analysis with pandas and numpy/scipy
- Data visualization with matplotlib/seaborn/plotly

Introductory readings
Book: “Python for Data Analysis”, 2nd Edition, Wes McKinney (2017). O'Reilly Media, ISBN: 9781491957660
Slides: “Python for data analysis” by Michele Tomaiuolo (UniPR)

Course requirements

Examination modality

Course material, enrollment and last minute notifications
Made available by the teacher at this Moodle address

11 Nov 2020, 10:00-13:00
13 Nov 2020, 10:00-13:00
18 Nov 2020, 10:00-13:00
20 Nov 2020, 10:00-13:00

Room 1BC50, Dept of Mathematics; Zoom link in case of quarantined students will be in the Moodle page of the course.

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