Dataset for: Electronic specific heat capacities and entropies from density matrix quantum Monte Carlo using Gaussian process regression to find gradients of noisy data

This dataset contains finite temperature specific heat capacities and entropies calculated using Gaussian process regression (GPR) applied to finite temperature density matrix quantum Monte Carlo data for several molecular benchmark systems and two systems beyond which exact data can be calculated. Additionally, for comparison, numerical and spline methods were used to approximate the specific heat and entropy similar to the GPR methodology. Finally, there is exact and approximate methods data for the same quantities, calculated using analytical expressions. This data was collected and discussed in the manuscript: "Electronic specific heat capacities and entropies from density matrix quantum Monte Carlo using Gaussian process regression to find gradients of noisy data", for more information see: https://doi.org/10.1063/5.0150702.