ENSO and MI

README: Enduring impacts of El Niño on life expectancy in past and future climates Overview This repository supports the analysis presented in the manuscript titled “Enduring impacts of El Niño on life expectancy in past and future climates”, which investigates the long-term impacts of El Niño–Southern Oscillation (ENSO) variability on mortality improvement, life expectancy, and associated economic costs. The repository includes all key analysis scripts, example data, and output figures necessary to reproduce the core results presented in the main text and supplementary figures. Repository Structure data.zip: Contains raw country-level mortality, economic, and health expenditure data used in the analysis. These data are unprocessed, and their official sources are fully cited in the Methods section of the manuscript. Supporting data folder contains pre-processed or testing datasets derived from the raw data sources, used for demo purposes and method validation. code.zip: Contains the full Python code used for analysis and figure generation. Each script corresponds to one or more figures in the manuscript (Fig. 1–3, S1–S15), and includes both analytical procedures and visualization routines. images.zip: Output directory that includes all generated figures. System Requirements Python version: 3.11.9 Required packages: pandas==2.2.3 numpy==2.0.2 statsmodels==0.14.4 scikit-learn==1.5.2 seaborn==0.13.2 matplotlib==3.9.2 No non-standard hardware or cloud services required. Installation Install Python (>= 3.11) Typical install time: 5 – 10mins Demo Create a virtual environment (recommended). Put the code and data in one folder. Run the selected script. Typical running time for each script: < 5 mins. Expected output as per depicted in the paper.