import pandas as pd
from sklearn.preprocessing import MinMaxScaler

def csv_to_featuers_list(csv_file):
    if csv_file == None:
        return ['No csv yet']
    df = pd.read_csv(csv_file)
    return df.columns

def pre_process_df(df):
    df.dropna(inplace=True)
    df.drop_duplicates(inplace=True)
    df.reset_index(inplace=True, drop=True)
    return df

def pre_process_features(X):
    scaler = MinMaxScaler()
    X = scaler.fit_transform(X)
    return X