This project explores factors affecting student performance across math, reading, and writing scores. Visualizations were created using Base R, ggplot2, TrelliscopeJS, and Plotly. Key variables analyzed include test preparation, parental education, sibling count, and sports participation. Each graph includes an investigation statement and analysis discussing how these variables relate to academic outcomes.

This analysis investigates the relationship between Power Consumption (kWh) and Temperature (°C) across three distinct zones, labeled Quads, Smir, and Boussafou. The data, collected over several time periods, includes power consumption data for each zone along with weather conditions such as Temperature and Humidity. The goal of this project is to visualize how temperature and humidity influence power consumption across these zones. The dataset gathered from Kaggle used for this analysis includes measurements taken at various times, detailing: Temperature (°C) Humidity (%) Power Consumption (kWh) for three zones: Quads, Smir, and Boussafou. Key Features: Hover Text: Users can hover over data points to view detailed information such as the Datetime, Temperature, Humidity, and Power Consumption for that specific point. Color Coding: The color gradient (yellow to purple) represents Humidity levels, allowing users to visually assess the relationship between humidity and power consumption. Animation: The plot cycles through the Zones (Quads, Smir, and Boussafou), making it easy to compare how power consumption changes across zones.

Using the trelliscopejs package to facet a chocolate sales analysis by country