Data Analysis with Python

In an effort to provide content for beginners, the book ‘Data Analysis with Python’ provides a concrete first step in learning data analysis. Written by a data professional with decades of experience, this book provides a solid foundation in data analysis and numerous data science processes. In doing so, readers become familiar with common Python libraries and straightforward scripting techniques.

Python and many of its well-known data analysis libraries, such as Pandas, NumPy, and Matplotlib, are utilized throughout this book to carry out various operations typical of data analysis projects.

Following an introduction to Python programming fundamentals, the book combines well-known numerical calculation and statistical libraries to demonstrate the fundamentals of programming, accompanied by many practical examples. This book provides a solid groundwork for data analysis by teaching Python programming as well as Pythons built-in data analysis capabilities.

KEY FEATURES

* Hands-on learning experience of Pythons fundamentals.
* Covers various examples of how to code end-to-end data analysis with easy illustrations.
* An excellent starting point to begin your data analysis journey with Python programming.

WHAT YOU WILL LEARN

* Learn the fundamentals of core Python programming for data analysis.
* Master Pythons most demanding data analysis and visualization libraries, including Pandas, NumPy, and Matplotlib.
* Refresh your step-by-step data analysis process with live examples.
* Extend your expertise to include real-time data analysis and the creation of simple Python scripts.
* Work with external files such as Excel, CSV, and others to clean them up for further analysis.

WHO THIS BOOK IS FOR

This book is intended to help and teach college students and data professionals about Pythons data analysis capabilities while also allowing them to work with Python tools.
Before diving into this book, working knowledge of Python is a definite plus.

1. Introducing Python
2. Environment Setup for Development
3. Operators and Built-in Data Types
4. Conditional Expressions in Python
5. Loops in Python
6. Functions and Modules in Python
7. Working with Files I/O in Python
8. Introducing Data Analysis
9. Introducing Pandas
10. Introduction to NumPy
11. Introduction to Matplotlib
12. Connecting Dots Step by step Data Analysis Hands-on Use Case

Rituraj Dixit is a seasoned software engineer who has been actively involved with developing solutions and architecting in the ETL, DWH, Big Data, Data on Cloud, and Data Science space for over a decade. He has worked with global clients and successfully delivered projects involving cutting-edge technologies such as Big Data, Data Science, Machine Learning, AI, and others.

He is passionate about sharing his experience and knowledge, and he trained newcomers and professionals across the globe. Currently, he is Associated as a Technical Lead with Cognizant Technology Solutions, Singapore.