Make tidy DataFrames from messy fit/model results.
Project description
Pybroom is a small python 3 library for converting fitting results (curve fitting or other optimizations) to Pandas DataFrame in tidy format (Wickham 2014). The DataFrames in tidy format (or long-form) 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 development was inspired by the R library broom. See this video for details of the philosophy behind broom and pybroom.
See the pybroom homepage for more info.
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