This report explores the six cleaned tables from the Global Civil Aviation Disruption 2026 dataset, analyzing the aviation impact of the February 2026 Iran-US conflict. Analysis covers conflict event severity and timing, flight cancellation trends by country and airline, airport operational status, airspace closure durations, airline financial losses, and reroute cost efficiency. Key findings include a dual-axis overlay of daily cancellations against critical conflict events, and interactive visualizations of airline loss vs passenger impact and reroute distance vs delay.

This report documents the cleaning and preparation of six relational CSV tables sourced from the Global Civil Aviation Disruption 2026 dataset (Kaggle). The dataset captures the aviation impact of the March 2026 Iran-US conflict, covering airspace closures, flight cancellations, reroutes, airport disruptions, airline financial losses, and conflict events across 25+ countries. Tables were joined using IATA codes, airline names, and country fields after standardizing inconsistent formats, extracting embedded identifiers, correcting typos, engineering datetime columns, and flagging data quality issues.

Six presentation-ready charts for a loan approval analysis — CIBIL score vs approval, approval rates by credit band, loan amount vs income scatter, approval by income bracket and education, cross-model feature importance, and ROC curve overlay. Built in a competition color palette with interactive plotly rendering and PNG exports for PowerPoint.

Three-model comparison for predicting loan approval outcomes (4,269 records). Covers logistic regression, decision tree, and random forest — each evaluated with a confusion matrix, feature importance plot, and ROC/AUC score. Built as a reusable modeling template for datathon competition prep.

Visual exploration of a loan approval dataset (4,269 records) covering target variable balance, numeric and categorical distributions, correlation heatmap, and bivariate analysis of key predictors against loan outcome. Built as a reusable EDA template for datathon competition prep.

Data cleaning workflow for a loan approval dataset (4,269 records). Covers column standardization, type conversion, missing value audit, outlier capping, and feature engineering. Built as a reusable template for datathon competition prep.

In this tutorial, we will cover the basics of data visualization using the ggplot2 package in R. We will create simple and informative visualizations, focusing on scatter plots, bar plots, and histograms.