diff --git a/presentation/event_stressfulness.py b/presentation/event_stressfulness.py
new file mode 100644
index 0000000..1f97c81
--- /dev/null
+++ b/presentation/event_stressfulness.py
@@ -0,0 +1,59 @@
+# ---
+# jupyter:
+#   jupytext:
+#     text_representation:
+#       extension: .py
+#       format_name: percent
+#       format_version: '1.3'
+#       jupytext_version: 1.13.0
+#   kernelspec:
+#     display_name: Python 3.10.8 ('straw2analysis')
+#     language: python
+#     name: python3
+# ---
+
+# %%
+# %matplotlib inline
+import datetime
+import importlib
+import os
+import sys
+
+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+import seaborn as sns
+import yaml
+from pyprojroot import here
+from sklearn import linear_model, svm, kernel_ridge, gaussian_process
+from sklearn.model_selection import LeaveOneGroupOut, LeavePGroupsOut, cross_val_score, cross_validate
+from sklearn.metrics import mean_squared_error, r2_score
+from sklearn.impute import SimpleImputer
+from sklearn.dummy import DummyRegressor
+import xgboost as xg
+
+from pathlib import Path
+
+nb_dir = os.path.split(os.getcwd())[0]
+if nb_dir not in sys.path:
+    sys.path.append(nb_dir)
+
+import machine_learning.features_sensor
+import machine_learning.labels
+import machine_learning.model
+import machine_learning.helper
+
+
+
+# %% tags=["active-ipynb"]
+# filename = Path("E:/STRAWresults/inputData/stressfulness_event/input_appraisal_stressfulness_event_mean.csv")
+
+# %%
+final_scores = machine_learning.helper.run_all_regression_models(filename)
+
+# %%
+final_scores.index.name = "metric"
+final_scores = final_scores.set_index(["method", final_scores.index])
+
+# %%
+final_scores.to_csv("event_stressfulness_scores.csv")