Description:

pdLSR 0.3.6

pdLSR
by Michelle L. Gill
pdLSR is a library for performing least squares regression. It attempts to
seamlessly incorporate this task in a Pandas-focused workflow. Input data
are expected in dataframes, and multiple regressions can be performed using
functionality similar to Pandas groupby. Results are returned as grouped
dataframes and include best-fit parameters, statistics, residuals, and more.
pdLSR has been tested on python 2.7, 3.4, and 3.5. It requires Numpy,
Pandas, multiprocess (https://github.com/uqfoundation/multiprocess), and
lmfit (https://github.com/lmfit/lmfit-py). All dependencies are installable
via pip or conda (see README.md).
A demonstration notebook is provided in the demo directory or the demo
can be run via GitHub (see README.md).

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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