Datasets:
File size: 1,185 Bytes
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import pandas as pd
import numpy as np
from rdkit import Chem
from rdkit.Chem import Descriptors
df_train = pd.read_csv("./intermediate/train.csv")
df_test = pd.read_csv("./intermediate/test.csv")
df_train = df_train.drop(['SMILES'], axis=1)
df_test = df_test.drop(['SMILES'], axis=1)
descriptor_names = [desc_name for desc_name, _ in Descriptors.descList]
len(descriptor_names)
def calculate_rdkit_descriptors(smiles):
mol = Chem.MolFromSmiles(smiles)
if mol is None:
return None
return {desc_name: func(mol) for desc_name, func in Descriptors.descList}
df_train_descriptors = df_train["Standardized_SMILES"].apply(calculate_rdkit_descriptors)
df_test_descriptors = df_test["Standardized_SMILES"].apply(calculate_rdkit_descriptors)
df_train_descriptors = pd.DataFrame(df_train_descriptors.tolist())
df_test_descriptors = pd.DataFrame(df_test_descriptors.tolist())
df_train_final = pd.concat([df_train, df_train_descriptors], axis=1)
df_test_final = pd.concat([df_test, df_test_descriptors], axis=1)
df_train_final.to_csv("./intermediate/train_rdkit_descriptors.csv", index=False)
df_test_final.to_csv("./intermediate/test_rdkit_descriptors.csv", index=False) |