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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

Additional text formats

Although text data can be viewed and read in a text editor, that doesn't mean it always contains plain text or simple columns of data. Two formats are encountered so often in today's projects that we need to spend some additional time studying them: JSON and HTML/XML. The JSON format is plain text but is structured much like a Python dictionary. Because it is plain text, it's easy to send and receive over internet connections, and because it has structure, it can encode complex table structures, including hierarchical or tree-like tables and other forms. You will find that many APIs use JSON by default, so you will likely encounter this format at some point. If you are reading data from a website, then it is likely encoded as HTML or XML data. In Exercise 3.01 – reading data from web pages, you saw a simple example of scraping a web page using .read_html().

Let's look at these formats in more detail.

Working with JSON

Let...

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