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Showing content from https://github.com/crosbyla/citrine_data_challenge below:

GitHub - crosbyla/citrine_data_challenge

This package uses the Pandas library to ingest GDB-9 XYZ structure files into the Physical Information Format (PIF). Metadata for the files is position-based, using the specification listed in Tables 2 and 3 at dx.doi.org/10.1038/sdata.2014.22.

Install using setup.py

$ python setup.py install

To use either import pandas_ingester module and use the available functions, or from the command line user the pandas-ingester utility:

$ pandas-ingester testfile.xyz

By default, the output file will be a JSON fill and will be written to the same directory. The file name will be based upon the gdb ID number. Optionally, one can specify the output file name with the -o flag:

$ pandas-ingester testfile.xyz -o outfile.json

The data used for tests is from the QM9 database from the article listed above. An example input data file can be found here. The corresponding output file can be found here.


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