如何在pandas df中并行循环两组列？

import pandas as pd
import multiprocessing as mp

df = pd.DataFrame({'A': [1, 2, 3, 4], 'B': [5, 6, 7, 8], 'C': [9, 10, 11, 12], 'D': [13, 14, 15, 16]})

def process_columns(cols1, cols2):
    for col1, col2 in zip(cols1, cols2):
        # 在这里执行你想要对两组列执行的操作
        print(col1, col2)  # 示例操作，打印两组列的名称

def parallel_process(df, process_func, num_processes):
    pool = mp.Pool(num_processes)
    num_cols = len(df.columns)
    num_cols_per_group = num_cols // 2

    # 将列分成两组
    cols1 = df.columns[:num_cols_per_group]
    cols2 = df.columns[num_cols_per_group:]

    # 并行处理两组列
    pool.starmap(process_func, [(cols1, cols2)])

    pool.close()
    pool.join()

parallel_process(df, process_columns, num_processes=2)