SURPY 1.1.5

SURPY python for surgical data analysis

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.soap_TU(data,oc,var)), soap_multi_T(data, oc) [fixed binary outcome tested on multiple continuous var] and soap_T_for_multibinary(data, var) [fixed continuous var tested against multiple binary variables at a time].

Comparison of distribution between groups using Chi-square test. (sp.soap_x_tab(data, var_a, var_b)) and (sp.soap_x_across(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%20070321SS.pdf