def feature_scale_or_normalize(dataframe, col_names, norm_type='StandardScaler'
    ):
    """
    Basically converts floating point or integer valued columns to fit into the range of 0 to 1
    """
    from sklearn.preprocessing import StandardScaler, MinMaxScaler
    if norm_type == 'StandardScaler':
        return StandardScaler().fit_transform(dataframe[col_names])
    elif norm_type == 'MinMaxScaler':
        return MinMaxScaler().fit_transform(dataframe[col_names])
    else:
        return None
