Force spectroscopy enables the experimental study of intermolecular and surface forces from molecular biology to hard material science, by measuring the interaction force versus the distance between the surfaces, called the separation. However, analyzing large datasets remains challenging. Here, we introduce a robust and fast method leveraging separation histograms to evaluate force gradients and average force profiles in force spectroscopy data. In experiments with constant driving velocity, an affine relationship between the separation histogram and the force gradient is demonstrated, enabling the reconstruction of forceseparation profiles with even spatial resolution and reduced noise. Additionally, two efficient averaging schemes are proposed, based on the cumulative separation histogram of a dataset and outperforming a conventional interpolation method. The procedures are illustrated with data obtained at the interface between an ionic liquid and a solid substrate by Atomic Force Microscopy, but are generic to all kinds of force spectroscopy techniques and systems.