Unit PYTHON LAB

Course
Finance and quantitative methods for economics
Study-unit Code
A003077
Location
PERUGIA
Curriculum
Data science for finance and insurance
Teacher
Davide Petturiti
Teachers
  • Davide Petturiti
Hours
  • 21 ore - Davide Petturiti
CFU
3
Course Regulation
Coorte 2022
Offered
2022/23
Learning activities
Altro
Area
Altre conoscenze utili per l'inserimento nel mondo del lavoro
Academic discipline
NN
Type of study-unit
Obbligatorio (Required)
Type of learning activities
Attività formativa monodisciplinare
Language of instruction
English
Contents
1. Introduction to Python
2. Control structures and programming
3. Functions and hints of object-oriented programming
4. Structured data types and containers
5. Access, manipulation and visualization of financial data
Reference texts
P.J. Deitel, H. Deitel: Intro to Python for Computer Science and Data Science, Pearson, 2020.

Y. Hilpisch: Financial Theory with Python – A Gentle Introduction, O'Reilly Media, 2021.

During the course, the teacher will provide didactic material, available in the UniStudium page of the course.
Educational objectives
At the end of the course students will possess and will be able to use the main Python programming tools, suitable to financial and actuarial applications.
Prerequisites
Basic knowledge of computer acquired during the Informatics course of the bachelor degree.
Teaching methods
The course is given in the form of practical lessons where teacher’s explanations are alternated to coding by students.

There will be exercise sessions finalized to complete small assignments and the treatment of examples of financial and actuarial applications.
Other information
Students can ask for further explanations (individually or in small groups) during lecturer's office hours, available at the link: https://sites.google.com/site/davidepetturiti/
Learning verification modality
The exam consists in a practical test of programming in Python language followed by a discussion of the written code.

The registration to exam must be through the site https://unipg.esse3.cineca.it/Home.do

Teaching material and other information on the course are available in the UniStudium page of the course.

Information on facilities for special needs students are available at the link https://www.unipg.it/en/international-students/general-information/facilities-for-special-needs-students
Extended program
1. Introduction to Python: characteristics of the language, distributions, code development and execution

2. Control structures and programming: variables and assignment, conditional structures, while and for cycles

3. Functions and hints of object-oriented programming: definition of functions, passing parameters, hints of classes and methods

4. Structured data types and containers: strings, sequences, dictionaries, arrays (NumPy library), Series and DataFrames (pandas library)

5. Access, manipulation and visualization of financial data: files, use of csv, yfinance, SciPy and Matplotlib libraries
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