This repo compiles published organic chemistry data, including raw data and calculated descriptor sets for molecules and reactions.

Each folder contains one reaction (see publication list for details).

Every reaction folder was divided into two sub-folders:

• mols: a list of molecules categorized by reaction roles)
• rxns: a list of reaction entries with multiple reaction components and yield).

import pandas as pd

REPO_PATH = 'https://raw.githubusercontent.com/beef-broccoli/ochem-data/main/'
FP = 'deoxyF/paper-dft/train.csv'  # change this  
df = pd.read_csv(REPO_PATH + FP)

# do things with df...

Each subfolder (ohe, mol2vec, mordred...) includes different descriptor encodings for the list of molecules or reaction entries

• deoxyF: Deoxyfluorination with Sulfonyl Fluorides: Navigating Reaction Space with Machine Learning

• Vbur: Linking Mechanistic Analysis of Catalytic Reactivity Cliffs to Ligand Classification

• CN: Predicting reaction performance in C–N cross-coupling using machine learning

• asym_epox: Ni/Photoredox-Catalyzed Enantioselective Cross-Electrophile Coupling of Styrene Oxides with Aryl Iodides

• CH-aryl-conditions: Bayesian reaction optimization as a tool for chemical synthesis

• kraken: A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis

• NiB: Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning

• Mordred: a molecular descriptor calculator
• Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition
• alvaDesc
• Kraken: A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis
• auto-qchem