- Docente: Paolo Foschi
- Credits: 3
- Language: Italian
- Moduli: Paolo Foschi (Modulo 1) Giulia Martielli (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
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Corso:
First cycle degree programme (L) in
Statistical Sciences (cod. 8873)
Also valid for Campus of Rimini
First cycle degree programme (L) in Statistics, Finance and Insurance (cod. 5901)
Campus of Rimini
Second cycle degree programme (LM) in Statistical, Financial and Actuarial Sciences (cod. 8877)
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from Sep 17, 2024 to Oct 15, 2024
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from Nov 07, 2024 to Dec 12, 2024
Course contents
Module 1:
- Introduction to Python: development environments for Python; Python language structure; basic data types: int, float, string; lists and tuples; mutable and immutable objects; if-then-else, for loops and function definitions.
- Scientific and Statistical Computing with Numpy and Scipy: extended floating point algebra; array creation and manipulation; arrays as objects and their properties; matrix products; code vectorialization; object distributions in Scipy, their properties and methods ; implementing a Monte Carlo simulation.
- matplotlib visualization.
Module 2:
- Introduction to Tableau: Tableau's tools (Desktop, Server, Public e Prep); tableau desktop interface overview; data import and connection from different data sources; dimensions and metrics; introduction to the data model (relations).
- Creation of simple visualizations: dispersion and bar plots; adding colors, shapes and labels; geographic maps, an introduction.
- Computed fields and other tools: personalized computations and computed fields (LOD?); hierarchies; sets; using filters and actions to add interactivity.
- Dashboard creation: fundamental concepts on data visualization and visual analysis; design and implementation of dashboards for presentations with multiple visualizations; adding global filters and interactivity between visualizations; optimization of visual aspect and dashboard arrangement.
- Dasboard Optimization and analysis distributon: exporting visualizations and dashboards to different formats; interactive dashboard publication on Tableau Server or Tableau Online.
Readings/Bibliography
Readings/Bibliography
* Transcript of the live tutorial
* Online:
- Introduction to Python: https://docs.python.org/3/tutorial/index.html
- Numpy Quickstart Guide: https://numpy.org/devdocs/user/quickstart.html
Teaching methods
Interactive laboratory tutorial lessons.
Assessment methods
* OnlineTest on EOL (esami online) Unibo's platform
* Development of a Project on Tableau
Teaching tools
- PC-Lab
- Google Colab platform
- Spyder IDE
- Tableau data analysis platform
- Microsoft Teams
Office hours
See the website of Paolo Foschi
See the website of Giulia Martielli