Python Data Analysis Cookbook

Standardizing reports, code style, and data access

Following a code style guide helps improve code quality. Having high-quality code is important if you want people to easily reproduce your analysis. One way to adhere to a coding standard is to scan your code with static code analyzers. You can use many code analyzers. In this recipe, we will use the pep8 analyzer. In general, code analyzers complement or maybe slightly overlap each other, so you are not limited to pep8.

Convenient data access is crucial for reproducible analysis. In my opinion, the best type of data access is with a specialized API and local data. I will introduce a dautil module I created to load weather data provided by the Dutch KNMI.

Reporting is often the last phase of a data ...