# B1578 - PYTHON LAB

• Docente: Silvia Cagnone
• Crediti formativi: 3
• Lingua di insegnamento: Inglese
• Modalità didattica: Convenzionale - Lezioni in presenza
• Campus: Bologna
• Corso: Laurea in Scienze statistiche (cod. 8873)

Valido anche per Laurea Magistrale in Statistical Sciences (cod. 9222)
• dal 06/05/2024 al 23/05/2024

## Conoscenze e abilità da conseguire

By the end of the course, the students know the basics of programming in Python and the usage of the main Python libraries for statistical analysis and acquire the skills to carry out case studies using the Python language.

## Contenuti

• Python programming
• Interactive programming environments
• Variables, expressions and types
• Lists and Dictionaries
• Conditional and loop statements
• Data handling with Pandas
• Pandas Dataframe
• Column and row handling
• Grouped Data
• Data ingestion .csv and .json files
• Data visualisation with Pandas and Seaborn
• Introduction to visualization
• Pandas plotting functions
• Seaborn plotting functions

## Testi/Bibliografia

• Python for Data Analysis, 3rd Edition, Wes McKinney, O'Reilly Media 2022. ISBN: 9781098104030
• https://www.python.org/
• https://pandas.pydata.org/
• https://seaborn.pydata.org/
• Better Data Visualizations, Jonathan Schwabish, Columbia University Press, 2021. ISBN: 9780231193115

## Metodi didattici

Lessons in lab held by prof. Carlos Gregorio Rodríguez.

The course is very practical. The concepts and ideas are tested and applied on a computer programming environment since the very beginning . The use of a computer/laptop is mandatory. The system requirements are simple: just a browser and internet connection.

The first week of the course will be on-line, the last two weeks in presence

## Modalità di verifica e valutazione dell'apprendimento

The assessment of the course is based on programming exercises that will be proposed. Students should submit their answers.

## Strumenti a supporto della didattica

• Google Colab is used. Online access with a browser in a computer is required.
• Teaching notes, exercises and other teaching materials provided by the instructor.
• Moodle virtual campus required to communicate with students and manage the assignments.

## Orario di ricevimento

Consulta il sito web di Silvia Cagnone