Chenometrics is a discipline that utilizes data mining techniques, including dimensionality reduction, discrimination, visualization, and regression, to extract information from extensive sets of experimental analytical data. NMR spectroscopy, a highly quantitative and reproducible technique, allows for non-invasive analysis of chemical species with minimal sample preparation. This is particularly advantageous for data mining, as NMR spectra, including series of 1H NMR spectra of biological samples, are commonly employed as input for multivariate analysis by converting series of 1D NMR spectra into a matrix. The 'Chemospec' package in the R language for statistical computing serves as the engine for multivariate analysis. When the 'Chempspec' package is installed, the Delta software offers a seamless user interface for exploratory multivariate analysis.