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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

Chapter 3 Conclusion

In this chapter, we embarked on a journey to understand the building blocks of Python programming, focusing on control structures, functions and modules, and Python scripting. We started by introducing you to control structures like loops and conditional statements. With just these tools, you can already construct quite powerful programs capable of performing repetitive tasks and making decisions.

The topic of functions and modules showed us how to package code into reusable units. This not only makes code easier to understand and maintain but also allows us to tap into a rich ecosystem of pre-built functions and modules available in Python's standard library and third-party packages. We've only scratched the surface here, but understanding these fundamental principles will serve you well as you dive into the more complex realms of data analysis.

Our final section on Python scripting covered the basics of script organization, command-line arguments, and...

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