def map_dtypes(categorical=[], string=[], numeric=[]):
    """Create dtype mapper for pd.read_csv to parse columns as specified dtypes

    Args:
        categorical, string, numeric (list): Column names to parse as type

    Usage:
        >>> dtype_mappevs codr = map_dtypes(categorical_columns=['gender', 'mood'])
        >>> df = pd.read_csv(csv_file.csv, dtype=dtype_mapper)
    """

    dtype_categorical = dict(zip(categorical, ["category" for i in range(len(categorical))]))
    dtype_numeric = dict(zip(numeric, ["float" for i in range(len(numeric))]))
    dtype_str = dict(zip(string, ["str" for i in range(len(string))]))
    dtype_mapper = {**dtype_categorical, **dtype_numeric, **dtype_str}

    return dtype_mapper