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Data Analysis Foundations with Python

You're reading from   Data Analysis Foundations with Python Master Data Analysis with Python: From Basics to Advanced Techniques

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Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781836209072
Length 551 pages
Edition 1st Edition
Languages
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Author (1):
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Cuantum Technologies LLC Cuantum Technologies LLC
Author Profile Icon Cuantum Technologies LLC
Cuantum Technologies LLC
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Toc

Table of Contents (37) Chapters Close

1. Code Blocks Resource
2. Premium Customer Support FREE CHAPTER
3. Who we are 4. Introduction
5. Who is This Book For? 6. How to Use This Book 7. Acknowledgments
8. Chapter 1: Introduction to Data Analysis and Python 9. Quiz for Part I: Introduction to Data Analysis and Python
10. Chapter 2: Getting Started with Python 11. Chapter 3: Basic Python Programming 12. Chapter 4: Setting Up Your Data Analysis Environment 13. Quiz for Part II: Python Basics for Data Analysis
14. Chapter 5: NumPy Fundamentals 15. Chapter 6: Data Manipulation with Pandas 16. Chapter 7: Data Visualization with Matplotlib and Seaborn 17. Quiz for Part III: Core Libraries for Data Analysis
18. Chapter 8: Understanding EDA 19. Chapter 9: Data Preprocessing 20. Chapter 10: Visual Exploratory Data Analysis 21. Quiz for Part IV: Exploratory Data Analysis (EDA)
22. Project 1: Analyzing Customer Reviews 23. Chapter 11: Probability Theory 24. Chapter 12: Hypothesis Testing 25. Quiz for Part V: Statistical Foundations
26. Chapter 13: Introduction to Machine Learning 27. Chapter 14: Supervised Learning 28. Chapter 15: Unsupervised Learning 29. Quiz Part VI: Machine Learning Basics
30. Project 2: Predicting House Prices 31. Chapter 16: Case Study 1: Sales Data Analysis 32. Chapter 17: Case Study 2: Social Media Sentiment Analysis 33. Quiz Part VII: Case Studies
34. Project 3: Capstone Project: Building a Recommender System 35. Chapter 18: Best Practices and Tips 36. Conclusion
37. Know more about us

2.1 Installing Python

Installing Python is a crucial first step in unlocking its immense potential for data analysis. The process itself is straightforward, but there are several different methods to achieve it. Depending on your specific needs, you may choose to install Python using one of several popular distributions such as Anaconda or Miniconda, which come preloaded with many of the most commonly used Python packages for data analysis.

Alternatively, you could opt to install Python directly from the official website, which provides more options but may require more manual configuration. For the purposes of this book, we will focus on the most direct and commonly used method of installing Python to ensure that you have the necessary tools to succeed in your data analysis journey.

2.1.1 For Windows Users:

  1. Download Installer: Go to the official Python website https://www.python.org/downloads/windows/.
  2. Run Installer: Once downloaded, locate the .exe file and double-click it.
  3. ...
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