ajout: restructuration du code

pyproject.toml

@@ -1,7 +1,12 @@
 [project]
 name = "projet-millesima-s6"
 version = "0.1.0"
-dependencies = ["requests==2.32.5", "beautifulsoup4==4.14.3", "pandas==2.3.3", "tqdm==4.67.3"]
+dependencies = [
+    "requests==2.32.5",
+    "beautifulsoup4==4.14.3",
+    "pandas==2.3.3",
+    "tqdm==4.67.3",
+]
 
 [project.optional-dependencies]
 test = ["pytest==8.4.2", "requests-mock==1.12.1", "flake8==7.3.0"]

src/cleaning.py

@@ -1,6 +1,5 @@
 #!/usr/bin/env python3
-from pandas import DataFrame, to_numeric
+from pandas import DataFrame, to_numeric, get_dummies
-import pandas as pd
 
 SCORE_COLS = ["Robert", "Robinson", "Suckling"]
 
@@ -51,8 +50,6 @@ def mean_score(df: DataFrame, col: str) -> DataFrame:
 
     means = means.rename(columns={col: f"mean_{col}"})
 
-    return means
-
 
 def mean_robert(df: DataFrame) -> DataFrame:
     return mean_score(df, "Robert")
@@ -99,7 +96,7 @@ def encode_appellation(df: DataFrame, column: str = "Appellation") -> DataFrame:
 
     appellations = df_copy[column].astype(str).str.strip()
 
-    appellation_dummies = pd.get_dummies(appellations)
+    appellation_dummies = get_dummies(appellations)
 
     df_copy = df_copy.drop(columns=[column])
 

src/main.py

@@ -5,13 +5,7 @@ from os.path import normpath, join
 from sys import argv
 from pandas import read_csv, DataFrame
 
-from cleaning import (display_info,
+from cleaning import *
-                      drop_empty_appellation,
-                      mean_robert,
-                      mean_robinson,
-                      mean_suckling,
-                      fill_missing_scores,
-                      encode_appellation)
 
 
 def load_csv(filename: str) -> DataFrame: