QM9PACK ✨

A Python package for data-mining the QM9 dataset

Installation details

Install Dependencies

• Ensure you have the following dependencies installed:
  • numpy
  • pandas
  • scipy
  • matplotlib

pip3 install numpy pandas scipy matplotlib

• If you want to convert a SMILES string to an SVG image, also install:
  • rdkit

Install directly from PyPI

   pip3 install qm9pack

Alternatively, download and Install the Package

Clone the repository and install the package:

git clone git@github.com:raghurama123/qm9pack.git
cd qm9pack
python3 -m pip install -e .

Tutorial

Click the image below for a PDF the latest version of the tutorial.

All the Python codes used in the tutorial are in the tutorials folder. The codes are named according to the section/subsection in the tutorial.

Support e-mail

ramakrishnan@tifrh.res.in raghu.rama.chem@gmail.com

How to cite?

If you find this module useful and have used it in your work, please cite it as

QM9PACK: A Python package for data-mining the QM9 dataset
Raghunathan Ramakrishnan
https://github.com/raghurama123/qm9pack

@misc{qm9pack,
  title   = {QM9PACK: A Python package for data-mining the QM9 dataset},
  author  = {Ramakrishnan, Raghunathan},
  year    = {2024},
  url = {https://github.com/raghurama123/qm9pack}
}

Additionally, please also cite the QM9 study

Quantum chemistry structures and properties of 134 kilo molecules
Raghunathan Ramakrishnan, Pavlo O. Dral, Matthias Rupp, O. Anatole von Lilienfeld
Scientific Data volume 1, Article number: 140022 (2014)

@article{ramakrishnan2014quantum,
  title={Quantum chemistry structures and properties of 134 kilo molecules},
  author={Ramakrishnan, Raghunathan and Dral, Pavlo O and Rupp, Matthias and Von Lilienfeld, O Anatole},
  journal={Scientific data},
  volume={1},
  number={1},
  pages={1--7},
  year={2014},
  publisher={Nature Publishing Group},
  url={https://doi.org/10.1038/sdata.2014.22}
}