python读取pickle,csv,excel文件速度大比拼

进行数据处理时数据量一大,excel文件就力不从心。
这次对三个文件格式的读取速度做大比拼。

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# -*- coding: UTF-8 -*-
import time
import pandas as pd
"""
csv
excel
pkl
速度大比拼

"""
start = time.clock()
df = pd.read_pickle('table.pkl')
elapsed = (time.clock() - start)
print("PKL Time used:", elapsed)

start = time.clock()
df = pd.read_csv('table.csv')
elapsed = (time.clock() - start)
print("CSV Time used:", elapsed)

start = time.clock()
df = pd.read_excel('table.xlsx')
elapsed = (time.clock() - start)
print("EXCEL Time used:", elapsed)

输出结果

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PKL Time used: 0.0913808
CSV Time used: 0.2128232
EXCEL Time used: 10.9964416

pickle完美胜出。参考链接中有大佬的更详细的比拼。

参考

https://www.jianshu.com/p/d857c0f472f4