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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

Introduction to pandas Series

In Chapter 5, Data Selection – DataFrames, we introduced several ways you can select data from pandas DataFrames. While a pandas Series can be thought of as a single column of a pandas DataFrame, it is a separate data structure. In this chapter, we are going to learn how to select data from a Series in detail. The key methods, such as .loc[] and .iloc[], will still apply to a one-dimensional Series, as well as some of the more advanced methods such as Boolean indexing and extended indexing. Now that you have mastered the methods you can apply to DataFrames, learning about Series will be very similar and intuitive. Toward the end of this chapter, we will spend some time understanding the differences between pandas and base Python regarding selecting data. This will reinforce some of the ideas and methods you have learned about. Conceptually, the same ideas we used to select elements from a DataFrame can be used to select elements from a Series....

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