semvec/pypi-packages huggingface dataset:
pandas-indexing 0.6.3
Helpers to facilitate working with pandas indices in particular multiindices
License: MIT
Requires Python: <4,>=3.9
Keywords: pandas

pandas-indexing helper
======================

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Summary
-------

``pandas-indexing`` is a helpers package to make interacting with pandas multi-indices less
painful. It contains functions, that

* filter easily into multi indices: ``isin``, ``ismatch``
* add or update levels in a multiindex: ``assignlevel``
* select one or multiple specific levels: ``projectlevel``

Usage
-----

Given you have a time-series like dataframe with several multi index levels, like ``model``, ``scenario``, ``variable``:
then you can select a subset with:

.. code:: python

    df.loc[isin(model="m1", scenario=["s1", "s2"])]

or with shell like glob-patterns:

.. code:: python

    df.loc[
        ismatch(
            model="REMIND*", variable="Emissions|**", unit=["Mt CO2/yr", "kt N2O/yr"]
        )
    ]

You can overwrite index levels:

.. code:: python

    assignlevel(df, selected=1)

or project your data to only a few desired index levels:

.. code:: python

    projectlevel(df, ["model", "scenario"])


All commands are described in detail in the API reference in `documentation`_ and are
togehter with introductions for installing and using this package, but they are mostly
bare-bones atm.

Issues and Discussions
----------------------

As usual for any GitHub-based project, raise an `issue`_ if you find any bug or
want to suggest an improvement, or open a discussion if you want to discuss.


.. _PyPI: https://pypi.org
.. _latest branch: https://github.com/coroa/pandas-indexing/tree/latest
.. _master branch: https://github.com/coroa/pandas-indexing/tree/master
.. _tox: https://tox.readthedocs.io/en/latest/
.. _ReadTheDocs: https://readthedocs.org/
.. _issue: htts://github.com/coroa/pandas-indexing/issues/new
.. _documentation: https://pandas-indexing.readthedocs.io/en/latest/
pincell-moment-utils 0.0.2
A tool for postprocessing and calculating flux moments for a pincell model
License: MIT
Requires Python: <4.0,>=3.8

# Introduction
This project primarily serves as a reference to the methods used to generate a moment dataset for parameterizing the incident and outgoing fluxes, as well as the local multiplication factor and the pin flux distribution for training a machine learning model to implement the incident flux response method. Included is also a utility package which was used to postprocess moment and mesh tallies and perform flux reconstruction from these moments following the theory described in `TODO`.

# Installation and Setup
This package is [published on PyPI](https://pypi.org/project/pincell_moment_utils/), and so can be installed (along with all of the necessary dependencies) via `pip`
```
pip install pincell_moment_utils
```
Note some of the features require the ability to run transport simulations with OpenMC, which require a valid set of cross sections, which can be installed using the scripts [here](https://github.com/openmc-dev/data).