在数据帧切片上并行化Pandas的正确方法

import pandas as pd
import numpy as np
from multiprocessing import Pool

def process_chunk(chunk):
    # 在这里进行自定义的处理操作
    grouped_data = chunk.groupby('column_name')
    result = grouped_data.sum()  # 示例操作：计算每个分组的总和
    return result

def parallelize_dataframe(df, num_partitions):
    chunks = np.array_split(df, num_partitions)
    pool = Pool(num_partitions)
    results = pool.map(process_chunk, chunks)
    pool.close()
    pool.join()
    return pd.concat(results)

# 示例用法
df = pd.read_csv('data.csv')
processed_df = parallelize_dataframe(df, num_partitions=4)