2025
Data Analysis for Economics and Business
Binder repository containing the notebooks for the R-coding sessions of the course Data Analysis for Economics and Business, taught to first-year B.Sc. in Finance students at ISEG (2025). These notebooks were developed with the idea of providing a first introduction to programming for undergraduate students, helping them build practical skills in data analysis. The materials cover five sessions introducing applied data analysis in R.
Topics covered:
- Set up; import, clean, and manage data.
- Basic programming concepts, data structures, and visualization (
ggplot2). - Descriptive statistics, group comparisons, inequality (Gini, Lorenz), and log transformations.
- Exploring relationships: scatter plots, correlation, and interpretation.
- Introduction to linear regression, coefficient interpretation, and reporting results.
You may also find here multiple-choice questions designed to assess key concepts in an introductory data analysis course. They are shared as a resource that may be useful for both students and instructors. Typos and errors are my own.
2024
Mapping Economic Landscapes
Material under eternal construction
Blends and extends the lecture notes of the Geographic Data Science for Public Policy Evaluation (AiREF - 2024) and Introduction to Python (CEMFI Diploma in Banking Supervision, 2024).
May be of interest to:
- Newcomers to geographic data science.
- Users of desktop GIS programms that want to shift to programming approahces.
- People interested in using geographic data tools for research or policy evaluation purposes.
Topics covered:
- Introduction to Python.
- Introduction to Geographic Data.
- Data Visualization with QGIS and Python.
- Processing and Analyzing Geographic Data with Python.