From 71acbf18860a1b50175d36136bef267dfddc3d0e Mon Sep 17 00:00:00 2001 From: Israel Figueroa Date: Sat, 18 Jan 2025 23:31:59 -0300 Subject: [PATCH] as --- load_dataset.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/load_dataset.py b/load_dataset.py index be214e4..1a4d9e2 100644 --- a/load_dataset.py +++ b/load_dataset.py @@ -79,7 +79,7 @@ def analisis_univariado(dfi, target=None, continuas=[], discretas=[]): resultsmody.append([ var, " ", f"{median1:.1f} ({ql1:.1f} - {qr1:.1f})", f"{median1:.1f} ({ql2:.1f} - {qr2:.1f})", - f"{t_pval:.3f}", ("*" if mw_pval < 0.05 else "NS"), f"{mediang:.1f} ({qlg:.1f} - {qrg:.1f})" + f"{mw_pval:.3f}", ("*" if mw_pval < 0.05 else "NS"), f"{mediang:.1f} ({qlg:.1f} - {qrg:.1f})" ]) # Análisis de variables discretas @@ -107,7 +107,7 @@ def analisis_univariado(dfi, target=None, continuas=[], discretas=[]): totf = 100 * tot / len(dfi[var]) resultsmody.append([ var, " ", f"{percentages[0][1]:.1f} ({freq_table[0][1]}/{len(group1)})", f"{percentages[1][1]:.1f} ({freq_table[1][1]}/{len(group2)})" - f"{t_pval:.3f}", ("*" if fisher_pval < 0.05 else "NS"), f"{totf:.1f} ({tot}/{len(dfi[var])})" + f"{fisher_pval:.3f}", ("*" if fisher_pval < 0.05 else "NS"), f"{totf:.1f} ({tot}/{len(dfi[var])})" ]) # Crear DataFrame con los resultados