pandas 分块读取大规模数据

__author__ = '未昔/angelfate'
__date__ = '2019/7/2 1:30'
# -*- coding: utf-8 -*-

path = r'E:\python\Study\BiGData\new_data.csv'
@timeit
def test_1():
    print('test_1')
    df = pd.read_csv(path, engine='python', encoding='gbk')


@timeit
def test_2():
    print('test_2')
    df = pd.read_csv(path, engine='python', encoding='gbk', iterator=True)  # 分块，每一块是一个chunk，之后将chunk进行拼接；

    loop = True
    chunkSize = 10000
    chunks = []
    while loop:
        try:
            chunk = df.get_chunk(chunkSize)
            chunks.append(chunk)
        except StopIteration:
            loop = False
            print("Iteration is stopped.")
    df = pd.concat(chunks, ignore_index=True)

test_1()
test_2()

这个是分别读取 1w 条数据的一个 csv 文件，所用的时间对比：