pybroom | pybroom , the python 's broom to tidy up messy fit results | Analytics library
kandi X-RAY | pybroom Summary
kandi X-RAY | pybroom Summary
pybroom, the python's broom to tidy up messy fit results!. Pybroom is a small python 3 library for converting fitting results (curve fitting or other optimizations) to Pandas DataFrame in tidy format (Wickham 2014). 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. Like the R library broom, pybroom provides 3 functions: tidy, augment and glance. For details see the documentation which includes example notebooks (you can find the source notebooks in docs/notebooks).
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Top functions reviewed by kandi - BETA
- Tidy result
- Concatenate multiple results
- Transforms lmfit result into a Pandas DataFrame
- Tidy a scipy result object
- Convert a dict to a pandas DataFrame
- Return a copy of the results
- Return a copy of var_names
- Wrapper for glance
- Convert lmfit result into a model instance
- Lookup a Scipy result
- Augment model results
- Augment lmfit model result
- Test if a dictionary contains keys and values
- Get the version number
pybroom Key Features
pybroom Examples and Code Snippets
Community Discussions
Trending Discussions on pybroom
QUESTION
My goal is to port a job that I have been doing in R over to Python. I know there are packages out there that would do what I need, but I have a difficult time translating what I may normally do in R to what needs to be done in Python. The scenario I'm dealing with is parallel to this one: R: Summarize inside an nlsLM() statement
I start with the following R dataframe:
...ANSWER
Answered 2019-May-10 at 19:13According to the documentation of pybroom
in this link, augment
won't work with the cuve_fit
function. You'll need to swap to using either lmfit
or just not use the augment
part at all.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install pybroom
You can use pybroom like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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