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| import pandas as pd | |
| from app.feature_engineering import transform_fe | |
| def test_transform_fe(): | |
| df = pd.DataFrame([{ | |
| "age": 30, | |
| "revenu_mensuel": 2500.0, | |
| "statut_marital": "Marié(e)", | |
| "departement": "IT", | |
| "poste": "Développeur", | |
| "annee_experience_totale": 5, | |
| "annees_dans_l_entreprise": 2, | |
| "annees_dans_le_poste_actuel": 2, | |
| "satisfaction_employee_environnement": 3, | |
| "note_evaluation_precedente": 4.2, | |
| "satisfaction_employee_nature_travail": 4, | |
| "satisfaction_employee_equipe": 4, | |
| "satisfaction_employee_equilibre_pro_perso": 3, | |
| "note_evaluation_actuelle": 4.5, | |
| "heure_supplementaires": "Oui", | |
| "augementation_salaire_precedente": "10%", | |
| "nombre_participation_pee": 1, | |
| "frequence_deplacement": "Rare", | |
| "annes_sous_responsable_actuel": 1 | |
| }]) | |
| out = transform_fe(df) | |
| # 1. La fonction renvoie bien un DataFrame | |
| assert isinstance(out, pd.DataFrame) | |
| # 2. Vérifier que les colonnes calculées existent | |
| assert "revenu_par_anciennete" in out.columns | |
| assert "ratio_exp_entreprise_externe" in out.columns | |
| assert "ratio_manager" in out.columns | |
| # 3. Vérifier que Oui -> 1 | |
| assert out.loc[0, "heure_supplementaires"] == 1 | |
| # 4. Vérifier que "10%" devient 10.0 | |
| assert out.loc[0, "augementation_salaire_precedente"] == 10.0 | |