Data Analysis with Python: Introducing NumPy, Pandas, Matplotlib, and Essential Elements of Python Programming

Data Analysis with Python: Introducing NumPy, Pandas, Matplotlib, and Essential Elements of Python Programming

English | 2022 | ISBN: 978-9355510655 | 276 Pages | EPUB | 10 MB

An Absolute Beginner’s Guide to Learning Data Analysis Using Python, a Demanding Skill for Today

Key Features

  • Hands-on learning experience of Python’s 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.

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 Python’s built-in data analysis capabilities.

What you will learn

  • Learn the fundamentals of core Python programming for data analysis.
  • Master Python’s 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.
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