Automated Mean ± SEM tables with statistical grouping letters in Python (pairwise tests, tidy data) v2

This protocol describes a reproducible Python workflow for generating publication-ready summary tables reporting mean ± SEM and statistical clustering letters for each experimental group. Starting from a tidy-long format CSV file (one row per observation), the workflow (i) calculates the group mean and standard error (SEM), (ii) evaluates pairwise differences between treatments (e.g., independent two-sample t-tests), (iii) converts the pairwise significance pattern into clustering letters (compact letter display concept), and (iv) exports a final large-format table in which each cell contains the mean ± SEM followed by superscript letters. The protocol is designed for multi-treatment datasets (e.g., A–I) and can be adapted to other factorial structures.