Introduction to tools for data analysis and information visualization
This curricular unit will present a variety of tools that can be used in the work routine of those who need to analyze data and create graphs and data visualizations. The curricular unit combines theoretical and practical aspects and does not require prerequisites. At the end of the course, students will have learned to:
- Extract data from documents, websites and social networks;
- Create graphics in different programming languages;
- Create interactive graphics;
- Create interactive maps.
Weekly - 1
Total - 140
- Matthes, E. (2019) Python Crash Course: A Hands-On, Project-Based Introduction to Programming. No Starch Press;
- Machlis, S. (2018) Practical R for Mass Communication and Journalism. Chapman and Hall/CRC;
- Murray, DS. (2017) Interactive Data Visualization for the Web: An Introduction to Designing with D3. O'Reilly Media;
- Murray, D. e Chabot C. (2013) Tableau Your Data!: Fast and Easy Visual Analysis with Tableau Software. John Wiley & Sons.
The curricular unit combines the exposition of theoretical knowledge with practical sessions. All students are expected to participate in the practical sessions and contribute to the discussion during the theoretical sessions.
Evaluation method -
Mini Tests(40%), Attendance and Participation(10%), Exam(50%)
The curricular unit "Introduction to tools for data analysis and information visualization" will serve to present several tools for data extraction and mining (Web Scraper, ParseHub, Octoparse, Scrapinghub, etc.); tools and languages for data analysis and graphing (Python, D3, R, HighCharts, etc.); tools for creating interactive graphs (Tableau, Datawrapper, Flourish, Raw Graphs, etc.); tools for creating interactive maps (Leaflet, Openheatmap, QGIS, Mapbox, etc.). In this curricular unit, students will have to carry out work with the tools presented.
Programs where the course is taught: