[SciPy-User] ANN: Pybroom, a python broom for tidying up messy fit results
(sorry for cross posting)
Announcing pybroom 0.1
I'm announcing the first public release of pybroom (version 0.1).
Any feedback or suggestions are welcome!
What is pybroom?
Pybroom is a small python 3 library for converting fitting results (curve fitting or other optimizations) to Pandas DataFrame in tidy format (or long-form).
DataFrames in tidy format follow a simple rule: one “observation” per row and one “variable” per column. This simple structure makes it easy to process the data with clear and well-understood idioms (for filtering, aggregation, etc.) and allows plot libraries to automatically generate complex plots in which many variables are compared. Plotting libraries supporting tidy DataFrames include seaborn, recent versions of matplotlib, bokeh and altair.
Pybroom was inspired by the R library broom. See this video for details of the philosophy behind broom:
Re: ANN: Pybroom, a python broom for tidying up messy fit results
This looks really nice - I will definitely use this.
Is there anything we should add to lmfit to make these tasks easier? Do you think there is anything that could be done to make ModelResult or similar "result" of a fit be made more "tidy" in this sense? Would it make sense to add a "tidy()" method to a ModelResult that did some of this work?