Una Infografía sobre los daños del Fracking en el agua

This report analyzes customer sentiment patterns in Flipkart product reviews using data visualization techniques in R. The project includes multiple visualizations to examine sentiment distribution, product ratings, review activity, and customer feedback trends across products. Interactive and static visualizations were created using ggplot2 and plotly as part of the Data Visualization Capstone project.

This is an exoplanet data analysis project that uses R to clean the dataset, explore planetary and stellar patterns, and build predictive models for astronomical insights.

PAF 516 Final Dashboard - Christopher Ogino

This chapter dives into the "engine room" of Data Science: Preprocessing. Students will learn that the quality of a model is determined long before it is trained, focusing on the critical steps required to turn messy, real-world data into a "model-ready" format. Core Topics covered: Why Preprocessing Matters Handling Missing Data Outlier Detection and Treatment Data Transformation Encoding Categorical Variables Feature Scaling Data Integration and Reshaping Chapter Lab Activity: Full Preprocessing Pipeline with msleep

This chapter addresses the foundational question of data science: "How do we ensure our data truly represents the world?" It explores the mechanics of selection, the math of sample size, and the power of computational resampling. Core Topics covered: Why Sampling Matters Probability Sampling Methods Non-Probability Sampling Methods Sample Size Determination Sampling Bias and Common Pitfalls Bootstrap Resampling Evaluating Sample Quality Chapter Lab Activity: Exploring Sampling with nhanes-Style Data