Python读取csv文件并提取数据到excel_python读取csv文件然后按行属性导出excel表格-优快云博客

本文链接：https://blog.youkuaiyun.com/github_53382513/article/details/111562419

为了工作需求，使用Python编写了一段脚本，该脚本能够读取csv文件中的fio性能数据，将其整理并输出到excel文件result.xlsx中，便于进行横向对比分析。fio数据包括filename、rw、bandwidth、iops和latency等字段，脚本还能够突出显示性能较低的数据。

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Python读取csv文件并提取数据到excel

背景：工作使然的缘故需要将存储跑出来大量的fio数据解析整理到excel，并将其中性能低的数据显著的显示出来，于是使用python写了一个数据处理的脚本。
输入：fio解析数据csv
输出：所有盘数据整理到excel横向对比result.xlsx
fio数据格式：
filename,rw,bandwidth(MB/s),iops,avg_latency(usec),max_latency(usec)
sdad_libaio_read_4K_1Job_1Dep_fio_read,read,68.58,16700.0,58.15,21439
sdad_libaio_read_4K_1Job_2Dep_fio_read,read,93.53,22800.0,85.84,29726
sdad_libaio_read_4K_1Job_4Dep_fio_read,read,95.21,23200.0,170.22,36416
sdad_libaio_read_4K_1Job_8Dep_fio_read,read,99.41,24300.0,327.80,35322
sdad_libaio_read_4K_1Job_16Dep_fio_read,read,100.87,24600.0,647.47,78942
sdad_libaio_read_4K_1Job_32Dep_fio_read,read,103.28,25200.0,1267.14,151885

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import csv #要处理的是csv文件
import sys
import os
import string
import fnmatch
import openpyxl   #python3 处理excel 模块
from openpyxl import Workbook
from openpyxl.styles import fills,colors,NamedStyle,Font,Side,Border,PatternFill,Protection,Alignment  #excel 单元格格式模块
#sys.path.append(os.path.abspath(__file__)
Cur_path = os.path.abspath('.')
width = 6 #excel cell (x,y)x=0,y=1 means A1
Title = ['Block size','IO type','WR/RD','Jobs','Queue Depth','bandwidth(MB/s)','IOPS']
excel_name = "result.xlsx"
def ex_file(mycsvfile, width):
    with open(mycsvfile,"r") as mycsvfile:
        if not os.path.exists(excel_name):
            workbook= Workbook()
            mysheet = workbook.create_sheet(title='sequence',index=0)
            workbook.create_sheet(title='random', index=1)
        else:
            workbook = openpyxl.load_workbook(excel_name)
            mysheet = workbook['sequence']
        #portion = os.path.splitext(mycsvfile)
        csvreader = csv.reader(mycsvfile)
        print(csvreader)
        row = 3
        row2 = 3
        count = 3
        count2 = 3
        for