I work at the intersection of data analysis, automation and engineering.
My background in infrastructure, observability and networks allows me to understand data not only from an analytical perspective, but also from how it is generated, transported and monitored in real systems.
I enjoy transforming raw, messy data into clean datasets, exploratory notebooks and actionable insights, always with a strong focus on reproducibility and engineering best practices.
- 📊 Exploratory Data Analysis using Python and Jupyter
- 🧹 Data cleaning, transformation and validation
- 🧠 Analytical thinking with an engineering mindset
- 🔁 Automation and reproducible workflows
- 📈 Turning data into insights that support decisions
A selection of hands-on notebooks focused on real data problems
- 📒 Exploratory Data Analysis
- Data understanding, cleaning and insight extraction
- 📊 Data Visualization Notebook
- Visual storytelling using Python
- 📐 Statistical Analysis
- Distributions, correlations and trends
- 🧼 Data Cleaning & Transformation
- From messy data to analysis-ready datasets
👉 Check them out here:
🔗 https://github.com/developreiloyo
- 🐍 PCAP-31-03 – Python Certified Associate Programmer (in progress)
- Continuous learning through hands-on projects and technical writing
