Book Image

The Pandas Workshop

By : Blaine Bateman, Saikat Basak, Thomas V. Joseph, William So
5 (1)
Book Image

The Pandas Workshop

5 (1)
By: Blaine Bateman, Saikat Basak, Thomas V. 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)
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

Summary

In this chapter, you saw how pandas supports data I/O to and from a wide variety of formats, both text and digital. You saw how pandas supports acting on multi-table databases in SQL directly from Python. You also explored the different character encodings that you may encounter in text data, as well as how to extract only the desired data columns from a more complex Excel file. Given the large amounts of data on the internet, you saw how pandas can extract tables from web pages and decode more complex web data in XML or JSON formats. You also learned how to use APIs to obtain data. In most cases, all you need is the pandas .read_xxx() and .to_xxx() methods. With what you have learned and practiced in this chapter, you are ready to handle most data sources you may encounter in your work.

Here, you've focused on getting data into and out of pandas DataFrames from a wide range of file types. In the next chapter, you will begin digging into the finer details and exploring...