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The Pandas Workshop

The Pandas Workshop

By : Blaine Bateman, Saikat Basak , Thomas Joseph, William So
4.8 (16)
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The Pandas Workshop

The Pandas Workshop

4.8 (16)
By: Blaine Bateman, Saikat Basak , Thomas Joseph, William So

Overview of this book

The Pandas Workshop will teach you how to be more productive with data and generate real business insights to inform your decision-making. You will be guided through real-world data science problems and shown how to apply key techniques in the context of realistic examples and exercises. Engaging activities will then challenge you to apply your new skills in a way that prepares you for real data science projects. You’ll see how experienced data scientists tackle a wide range of problems using data analysis with pandas. Unlike other Python books, which focus on theory and spend too long on dry, technical explanations, this workshop is designed to quickly get you to write clean code and build your understanding through hands-on practice. As you work through this Python pandas book, you’ll tackle various real-world scenarios, such as using an air quality dataset to understand the pattern of nitrogen dioxide emissions in a city, as well as analyzing transportation data to improve bus transportation services. By the end of this data analytics book, you’ll have the knowledge, skills, and confidence you need to solve your own challenging data science problems with pandas.
Table of Contents (21 chapters)
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1
Part 1 – Introduction to pandas
6
Part 2 – Working with Data
11
Part 3 – Data Modeling
15
Part 4 – Additional Use Cases for pandas

Chapter 14: Applying pandas Data Processing for Case Studies

So far in this book, we have progressively learned different data processing techniques using pandas, such as working with different types of data structures, accessing data from multiple sources, data cleaning, data transformation, visualization, code optimization, and finally, data modeling. This chapter aims to harness all these techniques you have learned so far, in analyzing four different case studies. The different case studies you will work through in this chapter will expose you to the different ways data needs to be preprocessed to be workable and help you see how good preparation is the key to good analysis. By the end of this chapter, you will have reinforced your understanding of all the data processing techniques you learned in this book by applying them to four case studies.

This chapter covers the following topics:

  • Introduction to the case studies and datasets
  • Recap of the preprocessing steps...

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