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Pandas 1.x Cookbook

Pandas 1.x Cookbook

By : Matthew Harrison, Theodore Petrou
4.5 (28)
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Pandas 1.x Cookbook

Pandas 1.x Cookbook

4.5 (28)
By: Matthew Harrison, Theodore Petrou

Overview of this book

The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter. This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. Many advanced recipes combine several different features across the pandas library to generate results.
Table of Contents (17 chapters)
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15
Other Books You May Enjoy
16
Index

Generating tests with Hypothesis

The Hypothesis library is a third-party library for generating tests, or performing property-based testing. You create a strategy (an object that generates samples of data) and then run your code against the generated output of the strategy. You want to test an invariant, or something about your data that you presume to always hold true.

Again, there could be a book written solely about this type of testing, but in this section we will show an example of using the library.

We will show how to generate Kaggle survey data, then using that generated survey data, we will run it against the tweak_kag function and validate that the function will work on new data.

We will leverage the testing code found in the previous section. The Hypothesis library works with pytest, so we can use the same layout.

How to do it…

  1. Create a project data layout. If you had the code from the previous section, add a test_hypot.py file...

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