diff --git a/tp6-preprocessing b/tp6-preprocessing
deleted file mode 100644
index 4aa01ec..0000000
--- a/tp6-preprocessing
+++ /dev/null
@@ -1,40 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-Created on Sun Jan  9 11:12:30 2022
-
-@author: pfaure
-"""
-from sklearn.neighbors import NearestNeighbors
-import numpy as np
-
-from myplotlib import print_1d_data, print_2d_data
-from mydatalib import extract_data_csv, scale_data
-
-path = './new-data/'
-dataset_name = "pluie"
-save = False
-
-print("-----------------------------------------------------------")
-print("     Chargement du dataset : " + dataset_name)
-(villes, data) = extract_data_csv(path + dataset_name, 13, 13)
-print(data)
-# print_2d_data(data, dataset_name=dataset_name +
-#              "_brutes", stop=False, save=save)
-
-print("-----------------------------------------------------------")
-print("     Mise à l'échelle")
-data_scaled = scale_data(data)
-# print_2d_data(data_scaled, dataset_name=dataset_name +
-#              "_scaled", stop=False, save=save)
-
-print("-----------------------------------------------------------")
-print("     Calcul du voisinage")
-n = 5
-neighbors = NearestNeighbors(n_neighbors=n)
-neighbors.fit(data_scaled)
-distances, indices = neighbors.kneighbors(data_scaled)
-distances = list(map(lambda x: sum(x[1:n-1])/(len(x)-1), distances))
-distances = np.sort(distances, axis=0)
-print_1d_data(distances, range(1, len(distances)+1), x_name="distance_moyenne",
-              y_name="nombre_de_points", stop=False, save=save)
diff --git a/tp-preprocessing b/tp6-preprocessing.py
similarity index 100%
rename from tp-preprocessing
rename to tp6-preprocessing.py