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The Pandas Workshop

You're reading from   The Pandas Workshop A comprehensive guide to using Python for data analysis with real-world case studies

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781800208933
Length 744 pages
Edition 1st Edition
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Authors (4):
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Blaine Bateman Blaine Bateman
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Blaine Bateman
William So William So
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William So
Saikat Basak Saikat Basak
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Saikat Basak
Thomas Joseph Thomas Joseph
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Thomas Joseph
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Toc

Table of Contents (21) Chapters Close

Preface 1. Part 1 – Introduction to pandas
2. Chapter 1: Introduction to pandas FREE CHAPTER 3. Chapter 2: Working with Data Structures 4. Chapter 3: Data I/O 5. Chapter 4: Pandas Data Types 6. Part 2 – Working with Data
7. Chapter 5: Data Selection – DataFrames 8. Chapter 6: Data Selection – Series 9. Chapter 7: Data Exploration and Transformation 10. Chapter 8: Understanding Data Visualization 11. Part 3 – Data Modeling
12. Chapter 9: Data Modeling – Preprocessing 13. Chapter 10: Data Modeling – Modeling Basics 14. Chapter 11: Data Modeling – Regression Modeling 15. Part 4 – Additional Use Cases for pandas
16. Chapter 12: Using Time in pandas 17. Chapter 13: Exploring Time Series 18. Chapter 14: Applying pandas Data Processing for Case Studies 19. Chapter 15: Appendix 20. Other Books You May Enjoy

Introduction to the world of pandas

Tess's latest project has turned out to be much more time-consuming than she initially anticipated. Her client, who develops and provides content for schools, wants her to find insights into their students' needs by analyzing data that's been collected through various sources. Things would have been much easier had this data been in a single format, but unfortunately, that's not the case. The client has sent her data in multiple formats, including HTML, JSON, Excel, and CSV. She has to extract the relevant information from all these files. These are not the only data sources she'll be working with, though. She also has to access the records of the top-performing and struggling students from a SQLite database so that she can analyze their performance patterns. All these disparate data elements differ in their data types, velocities, frequencies, and volumes. She must now extract different elements from these data sources by slicing, subsetting, grouping, merging, and reshaping the data to get a comprehensive list of features for further analysis. Since the volumes are large, she must also optimize her methods for efficient processing.

Does this scenario sound familiar to you? Are you overwhelmed by the data wrangling tasks that must be performed before the analytics processes? Well, you do not have to struggle anymore. pandas is a Python library that is capable of carrying out all these tasks and more. Over the years, pandas has become the go-to tool for all the preprocessing tasks involved in the life cycle of data analytics.

In this chapter, you will begin to explore and have fun with pandas, an amazing library that's used extensively by the data science and machine learning community. As you work through the exercises and activities in this chapter and the ones that follow, you will understand why pandas is considered the de facto standard when working with data. But first, let's take a short trip through time to understand the evolution of the library and get a glimpse into all the functionalities you will be learning about in this chapter.

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The Pandas Workshop
Published in: Jun 2022
Publisher: Packt
ISBN-13: 9781800208933
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