Use case: Working with different studies

[jurra]

(A study, is just a dataset of a sample population, say for example, dutch children, dutch adults)

I would like to normalize two datasets with different data structure, so that I can compare those sample populations.

As a designer/researcher I would like to compare two datasets, for example the percentiles of a certain measurement between two studies, or for two population, possibly from two different studies...

Acceptance criteria Given that the studies have different dimension/measurement names, while being the same measurement.

When running dined command or function, I can normalize or standarize those measurements under single name and definiti

Then we have two data series that are comparable.

• [ ] create Jupyter notebook
• [ ] Make design choice on data management in dined package
• [ ] create Jupyter notebook with dined calls

[toonhuysmans]

• [ ] An important consideration here is to think about the design of the data structure in python to store the measurements and to attach the measures and study meta data to it. The design should allow for easy combining of studies and filtering on certain measures.