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 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.

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.

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.