This project involves analyzing a flight dataset to predict delays using regression models. It includes data wrangling, transformation, and an introduction to Logistic Regression, KNN, and Naive Bayes models. The analysis will explore delays by reason and departure times, with performance visualized through confusion matrices. The data, sourced from the Bureau of Transportation Statistics, focuses on January and April 2022 flights from Atlanta by Delta, Spirit, and Frontier Airlines.
gdp-pop.Rmd: The R Markdown source file with the analysis code and narrative.gdp-pop.html: The rendered HTML file from the R Markdown document.energy-data.csv,gdp-pop.xlsx,Japan.xlsx,Germany.xlsx: Datasets for the analysis.
- This similar project can be found at [Kaggle] (https://www.kaggle.com/code/yomnanasseryounis/energy-consumption-data-visualization-tutorial/notebook)