Welcome to my personal blog. Here I share notes, tutorials, and workshop materials focused on programming in R, data wrangling, and spatial data analysis. Most of the content is in Spanish. Enjoy exploring!
1. Data Structures in R (in Spanish) — click here
This tutorial introduces the fundamental object types in R—such as vectors, matrices, and lists—through clear explanations and practical examples. It provides a foundational understanding of how data is structured and manipulated in R.
2. Tidy Data in R (in Spanish) — click here
This tutorial presents the principles of tidy data in R, emphasizing the importance of standardized data structure for efficient analysis. It illustrates how to reshape and organize datasets using the tidyverse framework.
3. Clonar Repositorios de GIT desde Rstudio (in Spanish) — click here
This tutorial provides a step-by-step guide on how to clone GitHub or GitLab repositories directly from RStudio. It is tailored for data science practitioners who want to integrate version control into their workflows. The post covers Git setup, repository connection, and practical tips for managing versioned R projects.
4. Introduction to Deepseek in R (in Spanish) — click here
This post provides a hands-on guide to installing and running large language models locally using Ollama. It highlights key steps and practical considerations for deploying models like LLaMA or Mistral on your own machine.
5. Introduction to Spatial Data in R (in Spanish) — Lecture (Part 1) - Lecture (Part 2) - R code
This two-part lecture introduces the fundamentals of spatial data analysis in R, covering key concepts such as coordinate reference systems, spatial objects, and visualization techniques using the sf and ggplot2 packages.
6. Introduction to Raster in R (in Spanish) — Lecture — Code
This post introduces the fundamentals of raster data in R, including structure, spatial resolution, and typical use cases. Through hands-on examples using the raster and terra packages, you’ll learn how to import, visualize, process, and analyze cell-based spatial data such as satellite imagery or elevation maps.
Ph.D. in Economics | Professor & Researcher | Big Data & Machine Learning