This repository includes the interactive map in format .html of the very first application of the Heat Stress Compensability Classification (HSCC) in 96 cities in the United States showing the proportion of days with compensable and uncompensable heat stress from the top 10th percentile of hottest days from 2005-2020 in each place. This map offers the detailed results of the very first application of the classification system as in the journal article: The Development of an Adaptive Heat Stress Compensability Classification Applied to the United States, published in the 4th SNP special issue in the International Journal of Biometeorology. The results of this visualization were obtained from open-source data and coding packages such as Folium, and the model results were obtained by applying the Python Human Heat Balance (PyHHB) on weather dataset freely available. The interactive map offers a detailed visualization of the results from each of the cities, allowing you to see 3 tabs when the icon of the pie chart from each location is clicked. Tab statistics: Detail per city of Figure 4b of related paper. Tab Histogram 2D: Details per city of Fig 6 of related paper Tab How to read: Figure 2 in related paper. Please for questions related to this dataset/code contact Gisel Guzman-Echavarria (gguzma20@asu.edu). Guzman-Echavarria, G., & Vanos, J. (2023). PyHHB: Physiological-based estimations of human survivability and liveability to heat in a changing climate (Nature Communications (1.0.0)). Zenodo. https://doi.org/10.5281/zenodo.10020137