This repository contains a Python implementation of Principal Component Analysis (PCA) for dimensionality reduction and variance analysis. PCA is a powerful statistical technique used to identify patterns in data by transforming it into a set of orthogonal (uncorrelated) components, ranked by the amount of variance they explain.

A comprehensive guide to visualizing data with Matplotlib, from basic plotting techniques to advanced customization, for effective data storytelling in data science and analysis.

This project was for exploring and visualizing the sales data of a tech store. This project’s main focus was to clean the data, prepare it for analysis, explore and visualize the data given in the forms of many CSV files.

This project aims to uncover the factors behind high cancellation rates in City & Resort Hotels, enabling data-driven strategies to enhance revenue and room utilization.