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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

Exploring data sources

Data can be obtained from a variety of sources, such as files on your computer, files on your company network, files in the cloud (such as Amazon AWS S3 storage), and web sources. You saw CSV files that contain data as text in the previous chapter. Now, let's consider different types of data that may appear in files.

Text files and binary files

You are already familiar with text files. A simple definition, albeit a bit circular, is that if you can open, read, and understand data in a text editor (such as Notepad on Windows, Notepad++, or other similar applications), you are dealing with text data. For example, in Chapter 2, Data Structures, you worked with small files that contained sales records of pet foods. If you open dog_food_orders.csv (located in the Chapter02/Datasets folder) in a text editor (here, Notepad in Windows), you will see the following:

Figure 3.3 – The dog_food_orders.csv file as a text file

Here...

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