Use label encoding for categorical attributes

src/preprocessing.py

@@ -16,11 +16,15 @@ def process_na(df, action):
 
 
 def encode_columns(df):
-    encoder = LabelEncoder()
-    encoder.fit(df["Shape"])
+    label_encoder = LabelEncoder()
+    encoded_df = df.copy()
+    encoded_df["Shape"] = label_encoder.fit_transform(df["Shape"])
+    encoded_df["Severity"] = label_encoder.fit_transform(df["Severity"])
+    return encoded_df
 
 
 def parse_data(source, action):
     df = read_csv(filepath_or_buffer=source, na_values="?")
-    processed_df = process_na(df, action)
-    return processed_df
+    processed_df = process_na(df=df, action=action)
+    encoded_df = encode_columns(df=processed_df)
+    return encoded_df