In which ways could object-orientation (OO) make my data analysis more efficient and let me reuse more of my code? The data analysis can be broken up into
- get data (from db or csv or similar)
- transform data (filter, group/pivot, ...)
- display/plot (graph timeseries, create tables, etc.)
I mostly use Python and its Pandas and Matplotlib packages for this besides some DB connectivity (SQL). Almost all of my code is a functional/procedural mix. While I have started to create a data object for a certain collection of time series, I wonder if there are OO design patterns/approaches for other parts of the process that might increase efficiency?