Add basic preprocessing functions

src/preprocessing.py

@@ -0,0 +1,29 @@
+from pandas import DataFrame, read_csv
+from sklearn.preprocessing import normalize
+from sklearn.model_selection import KFold
+
+
+def replace_values(df) -> DataFrame:
+    for column in df.columns:
+        df[column].fillna(value=df[column].mean(), inplace=True)
+    return df
+
+
+def remove_letters(df) -> DataFrame:
+    columns = ["Consumo", "Motor_CC", "Potencia"]
+    processed_df = df.copy()
+    for col in columns:
+        processed_df[col] = df[col].str.replace(pat="[^.0-9]", repl="").astype(float)
+    return processed_df
+
+
+def split_k_sets(df):
+    k_fold = KFold(shuffle=True, random_state=42)
+    return k_fold.split(df)
+
+
+def parse_data(source) -> DataFrame:
+    df = read_csv(filepath_or_buffer=source, na_values="?")
+    processed_df = df.dropna()
+    numeric_df = remove_letters(processed_df)
+    return numeric_df