2. The correlation analysis of the output data consists of the input spectrum, the fit, the residuals, and the single contributions. The Pearson-type correlation analysis is performed by the Pandas package. Based on the correlation analysis, the user can check whether the fit is reasonable and whether individual contributions are correlated with each other. In Figure , the concept of correlation analysis is demonstrated, whereas Figure provides a practical illustration of the fit of complex 1. Figure The reference example depicted in Figure has been resolved through the utilization of the intensity data, the best fit, six peaks (Gaussian distributions), and background correction, as evidenced by the figure on the left. The corresponding heatmap on the right-hand side excludes energy and residual. Both visualizations have been generated through the employment of Spectrafit's auto-export feature. Notably, two observations of significance emerge: Firstly, the linear correlation between intensity and fit is high, exceeding 100%, which is ideal. Secondly, peaks 4, 5, and 6, in combination with the cumulative Gaussian distribution, exhibit a correlation of more than 50%, thus rendering them valuable inputs for further optimization efforts. Adapted from Ref. ; Copyright 2023 America Chemical Society (ACS).