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Not available digitally or on paper through the Noor Library, it is for rating and review
| Author: | Mohammad Belal Ansari |
| Category: | Python Programming Language [Edit] |
| Language: | English |
| Rank: | 1,078,834 No 1 most popular |
| Short link: | Copy |
| More books like this book | |
The Publisher and the author
Book Python for Data Analysis .
Mohammad Belal Ansari is an independent researcher, science writer, and entrepreneur with a strong interest in physics, cosmology, climate technology, and emerging scientific ideas. He holds a Master's degree in Physics and is passionate about making complex scientific concepts accessible to a wider audience.
His work explores some of the most profound questions in modern science, including the nature of time, relativity, quantum mechanics, black holes, consciousness, and the future of the universe. Through his writing, he aims to bridge the gap between advanced scientific research and curious readers seeking to understand the mysteries of reality.
In addition to his work as an author, Mohammad Belal Ansari is the founder of Ecoso Next Generation Pvt. Ltd., a climate-tech venture focused on innovative approaches to carbon capture and sustainable technologies.
He believes that science is not merely a collection of facts but a journey of discovery that expands our understanding of the universe and our place within it.
When he is not writing or researching, he explores new ideas at the intersection of physics, technology, environment, and innovation.
Data is transforming the world, and the ability to analyze it has become one of the most valuable skills of the modern era.
Whether you are a student, researcher, business professional, or aspiring data analyst, Python for Data Analysis provides a practical and accessible path to mastering the tools and techniques used by data professionals worldwide.
Designed for beginners and intermediate learners, this comprehensive guide takes you from Python fundamentals to real-world data analysis projects. You will learn how to collect, clean, transform, visualize, and analyze data using industry-standard libraries and workflows.
Through clear explanations, practical examples, and hands-on projects, you will develop the skills needed to turn raw data into meaningful insights and build predictive models with confidence.
Inside this book, you will learn how to:
Work with Python for data analysis from the ground up
Use NumPy and Pandas to manipulate and analyze datasets efficiently
Clean and prepare real-world data for analysis
Create compelling visualizations with Matplotlib and Seaborn
Explore data using descriptive statistics and exploratory data analysis techniques
Query and analyze data stored in SQL databases
Retrieve and process information from APIs and web sources
Build, evaluate, and deploy machine learning models using Scikit-learn
Create end-to-end data analysis workflows and real-world projects
Apply industry best practices for reproducible and efficient analysis
No prior experience in programming or data analysis is required.
By the end of this book, you will have a strong foundation in Python, practical experience working with real datasets, and the confidence to solve data-driven problems across business, research, finance, healthcare, marketing, and many other fields.
If you are ready to transform raw data into actionable insights, this book will guide you every step of the way.
Turn data into insights. Build skills. Solve real-world problems.
Copyright reserved
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