From 2a9a5259c7f2c1d6d33402f8e4cb64c5c8a924f5 Mon Sep 17 00:00:00 2001 From: Denys Herasymuk Date: Sat, 14 Sep 2024 14:56:32 +0300 Subject: [PATCH] Added a tutorial on how to use PyTorch Tabular models together with Virny --- virny/custom_classes/metrics_visualizer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/virny/custom_classes/metrics_visualizer.py b/virny/custom_classes/metrics_visualizer.py index 75a531c0..d63ec175 100644 --- a/virny/custom_classes/metrics_visualizer.py +++ b/virny/custom_classes/metrics_visualizer.py @@ -52,7 +52,7 @@ def __init__(self, models_metrics_dct: dict, models_composed_metrics_df: pd.Data for model_name in model_names: columns_to_group = [col for col in models_metrics_dct[model_name].columns if col not in ('Model_Seed', 'Run_Number')] - models_average_metrics_dct[model_name] = models_metrics_dct[model_name][columns_to_group].groupby(['Metric', 'Model_Name']).mean().reset_index() + models_average_metrics_dct[model_name] = models_metrics_dct[model_name][columns_to_group].groupby(['Metric', 'Model_Name']).mean(numeric_only=True).reset_index() # Create one average metrics df with all model_dfs models_average_metrics_df = pd.DataFrame()