Getting in a public university in Greece requires candidates to take the Panhellenics examination. Your average grades from the exam, must be above the university's required minimum grade. That required minimum grade changes every year, so I made this script that forecasts that grade for next year. Accuracy has not been proven yet!

gpa_forecast.py

import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import PolynomialFeatures

years = np.array(range(2004, 2024)).reshape(-1, 1)
required_gpa = np.array(
    [17.1, 17.1, 16.8, 17.1, 17.1, 17.6, 17.8, 16.3, 16.3, 15.5, 16.3, 16.0, 16.0, 15.8, 16.4, 16.7, 16.8, 17.3, 17.1,
     17.7]) # Change me!

poly = PolynomialFeatures(degree=2)
X_poly = poly.fit_transform(years)
model = LinearRegression()
model.fit(X_poly, required_gpa)

next_years = np.array([2024, 2025, 2026]).reshape(-1, 1)
next_years_poly = poly.transform(next_years)
predicted_gpa = model.predict(next_years_poly)

for year, gpa in zip(next_years, predicted_gpa):
    print(f"Estimated required GPA for {year}: {gpa:.2f}")