Metadata-Version: 2.1
Name: pygeochemtools
Version: 0.1.2
Summary: An eclectic set of geochemical data manipulation, QC and plotting tools.
Home-page: https://github.com/RADutchie/pygeochemtools
Author: Rian Dutch
Author-email: riandutch@gmail.com
License: MIT
Project-URL: Documentation, https://pygeochemtools.readthedocs.io/en/latest/
Project-URL: Blog, https://geodataanalytics.net/
Keywords: geology,earth science,geoscience,exploration,geochemistry
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: click (>=8)
Requires-Dist: numpy (>=1.20)
Requires-Dist: pandas (>=1.2)
Requires-Dist: dask (>=2021.6)
Requires-Dist: matplotlib (>=3.3)
Requires-Dist: metpy (>=1.0)
Requires-Dist: PyYAML (>=5.0)
Requires-Dist: rich (>=10.13)
Provides-Extra: cartopy
Requires-Dist: Cartopy (>=0.19.0.post1) ; extra == 'cartopy'

pygeochemtools
===============

*A CLI based eclectic set of geochemical data manipulation, QC and plotting tools.*

*Pygeochemtools* is a python library and command line interface tool to enable rapid manipulation, filtering, QC and plotting
of geochemical data. It is primarily designed to allow people with limited or no coding experience to deal with
very large datasets when programs like Excel will struggle. It is designed to natively load and manipulate the geochemical datasets output by the Geological
Survey of South Australia, but will easily handle other datasets with a little bit of configuration in later updates.

Why *pygeochemtools*
----------------------

The SA Geodata database (available via the [SARIG](https://map.sarig.sa.gov.au/) portal) contains over 10 Gb of geochemical data.
That’s a lot of chemistry. Explorers often request extracts of this data set, but then find it a challenge to handle all that data.
Because of the size and amount of data, programs like Excel wont even open the file, and if the extract is small enough to open,
explorers often find the format of the data a challenge. Generally, people like to use wide data for analysis, where each row in a
table represents all the data about a single sample. But database exports are in a long format where each row represents a single data point.

*Pygeochemtools* provides an abstraction and cli to make loading, filtering and restructuring this data easy. It uses python libraries
like dask and pandas under the hood to be able to deal with 'larger than memory' datasets, so you can load and filter those large datasets
and then output something more easy to handle with Excel or other tools.

Functionality
---------------

Currently *pygeochemtools* provides the following functionality:
   - Filter large datasets based on a list of elements, sample type or drillhole numbers (or a combination of all three) and convert from long to wide format.
   - Add detailed geochemical methods columns onto the SARIG geochemical dataset.
   - Extract single element datasets from large geochemical datasets.
   - Plot maximum down hole geochemical data maps.
   - Plot maximum down hole chemistry per interval geochemical data maps.


