SURPY python for surgical data analysis
Project description
Surgical-Python (soap) is a collection of Python commands intended to be used for Surgical Outcome Data Analysis, from data importing, cleaning-up, merging data-frame, analysis and visualization. (from SURPY import soap as sp) Data importing from Excel file, followed by data exploration. (sp.soapsheetin(path)) Data scan. (sp.soapplore(data, oc)) Comparison of parametric/non-parametric data between 2 groups of the outcome (sp.soaptu(data,oc,var)) and (sp.soapvarin() followed by sp.soaptumulti(data,oc,factors)) Comparison of distribution between groups. (sp.soapbivarin(data) followed by sp.soapxtab(data, var_a, var_b)) and (sp.soapxtabax(data,outcome)) Survival curve drawing (sp.single_kmc(data, status, interval)) and survival comparisons (sp.compare_kmc(data, factor, status, interval)
for manual, go to: https://github.com/sasurasa/Surgical-Outcome-Analysis-on-Python/blob/SURPY/SURPY%20manual%20040321SS.pdf
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