Includes appendix and index.

"Hands-on Exploratory Data Analysis with Python" by Mukhiya and Ahmed provides a practical guide to mastering EDA techniques. The book emphasizes a hands-on approach, utilizing Python libraries like PyPlot, NumPy, SciPy, pandas, Matplotlib, and Seaborn. It covers the core aspects of EDA, from data cleaning and preparation to exploration and visualization. Readers learn to analyze open-source datasets, progressing from basic descriptive statistics to advanced time-series analysis. A key focus is on using EDA for model development and evaluation, culminating in building predictive models and visualizing results. The book explores data wrangling, handling missing values, identifying correlations, and performing graphical analysis. It also delves into multiple regression, hypothesis testing, and time-series analysis. Practical examples and real-world datasets are used throughout, making the concepts accessible. The book is designed for individuals interested in data analysis, including students, statisticians, data analysts, and data scientists, assuming basic Python programming and statistical knowledge. It equips readers with the skills to investigate datasets, extract insights, present findings visually, and build predictive models for informed decision-making.