🏃‍♀️ Process, Visualize, and Analyze Actigraphy Data

This repository contains resources and code examples related to Feature Engineering and Exploratory Data Analysis (EDA) techniques in the field of data science and machine learning.

Java/Spring Boot + Swing desktop app for cleaning and interpolating time-series CSV data. Automatically detects intervals, fills missing timestamps, preserves keywords, computes per-column statistics, and uploads cleaned files to AWS S3. Supports large datasets (800+ columns, 120+ hours).

A PySpark-based solution for cleaning and interpolating battery sensor data using forward/backward fill and Radial Basis Function (RBF) spatial interpolation. Outputs a clean, fully interpolated dataset in CSV format for advanced analysis.

A Brazil climate estimate cluster analysis from 11 year INMET spatio-temporal meteorological data.