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...