Método Tornado como marco gráfico exploratorio para distribuciones discretas Con numero primos

This manuscript presents the Tornado Method as a computational and graphical framework for visual inspection, exploratory data analysis, and anomaly detection in discrete frequency distributions. The methodology formalizes rules for transforming numerical datasets through digit sums and digital roots, representing exact counts for each target through ellipses whose areas are strictly proportional to the observed frequencies. As a numerical reference and case study, prime number sequences of up to one million are analyzed, documenting exact arithmetic restrictions and distribution convergence. Furthermore, a statistical control scheme is integrated through the total variation distance ($D_{TV}$) and Monte Carlo simulations to calibrate tolerances, evaluate sensitivity to data perturbations, establish negative controls, and define the identifiability limits of the method.