Book Image

Pandas 1.x Cookbook - Second Edition

By : Matt Harrison, Theodore Petrou
Book Image

Pandas 1.x Cookbook - Second Edition

By: Matt 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)
15
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16
Index

Using pytest with pandas

In this section, we will show how to test your pandas code. We do this by testing the artifacts. We will use the third-party library, pytest, to do this testing.

For this recipe, we will not be using Jupyter, but rather the command line.

How to do it…

  1. Create a project data layout. The pytest library supports projects laid out in a couple different styles. We will create a folder structure that looks like this:
    kag-demo-pytest/
    ├── data
    │ └── kaggle-survey-2018.zip
    ├── kag.py
    └── test
        └── test_kag.py
    

    The kag.py file has code to load the raw data and code to tweak it. It looks like this:

    import pandas as pd
    import zipfile
    def load_raw(zip_fname):
        with zipfile.ZipFile(zip_fname) as z:
            kag = pd.read_csv(z.open('multipleChoiceResponses.csv'))
            df = kag.iloc[1:]
        return...