京公网安备 11010802034615号
经营许可证编号:京B2-20210330
python处理csv数据的方法
本文实例讲述了python处理csv数据的方法。分享给大家供大家参考。具体如下:
Python代码:
代码如下:
#coding=utf-8
__author__ = 'dehua.li'
from datetime import *
import datetime
import csv
import sys
import time
import string
import os
import os.path
import pylab as plt
rootdir='/nethome/dehua.li/orderlifeCycleData/xingzheng'
writeFileDir="/nethome/dehua.li/orderlifeMyWork/xingzheng/csv"
heyueFile="/nethome/dehua.li/orderlifeCycleData/heyue_150128.csv"
ms_acked="1"
msg=[]
ex=[]
def getTheDate(date):
[filenamePart1,filenamePart2]=string.split(filename,'.')
[filenamePart11,filenamePart12,filenamePart13]=string.split(filenamePart1,'_')
return filenamePart13
LocalTime=datetime.datetime.fromtimestamp(time.mktime(time.strptime("2014-11-04 20:59:59","%Y-%m-%d %H:%M:%S")))
for parent,dirname,filenames in os.walk(rootdir):
for filename in filenames:
fileNameWrite=os.path.join(writeFileDir,filename)
print fileNameWrite
csvfile00=open(fileNameWrite,'wb')
writer1=csv.writer(csvfile00)
writer1.writerow(['FeedCode','OrderId','Status','LocalTime','Time','Exchange'])
fileName=os.path.join(parent,filename)
[filenamePart1,filenamePart2]=string.split(filename,'.')
[filenamePart11,filenamePart12,filenamePart13]=string.split(filenamePart1,'_')
#filenamePart11_filenamePart12_filenamePart13.filenamePart2:dongzheng_orderlifeCycleData_20150111.csv
print fileName
with open(fileName,'rb') as csvfile:
reader=csv.reader(csvfile)
CsvItem=[row for row in reader]
for item in CsvItem:
if item[3]=='TPO':
#print " filter TPO "
continue
if item[12]=='Sent':
[tm_local,ms_local]=string.split(item[15],'.')
[tm_localup,ms_localup]=string.split(item[19],'.')
LocalTime=datetime.datetime.fromtimestamp(time.mktime(time.strptime(tm_local,"%Y-%m-%d %H:%M:%S")))
LocalUpdate=datetime.datetime.fromtimestamp(time.mktime(time.strptime(tm_localup,"%Y-%m-%d %H:%M:%S")))
tm=int(((LocalTime-LocalUpdate).seconds))*1000
ms_sent=str(int(ms_local)-int(ms_localup)+tm)
if int(ms_sent)>10*60*1000:
print "ms_sent>600000"
continue
if(int(ms_local)-int(ms_localup)+tm)<0:
print 'wrong1'
msg=[]
msg.append(item[0])
msg.append(item[1])
msg.append(item[12])
msg.append(item[15])
msg.append(ms_sent)
with open(heyueFile,'rb') as csvfile1:
reader=csv.reader(csvfile1)
CsvItem=[row for row in reader]
for Item in CsvItem:
if Item[1]==item[0]:
msg.append(Item[3])
writer1.writerow(msg)
#print 'write ok'
ex=Item[3]
break
csvfile1.close()
with open(fileName,'rb') as csvfile22:
reader=csv.reader(csvfile22)
CsvItem2=[row for row in reader]
for item_ in CsvItem2:
if item_[12]=='Acked' and item_[1]==item[1]:
[tm_local2,ms_local2]=string.split(item_[15],'.')
LocalTime2=datetime.datetime.fromtimestamp(time.mktime(time.strptime(tm_local2,"%Y-%m-%d %H:%M:%S")))
tm2=int(((LocalTime2-LocalTime).seconds))*1000
ms_acked=str(int(ms_local2)-int(ms_local)+tm2)
if int(ms_acked)>10*60*1000:
print "MSacked>600000"
continue
msg=[]
msg.append(item_[0])
msg.append(item_[1])
msg.append(item_[12])
msg.append(item_[15])
msg.append(ms_acked)
with open(heyueFile,'rb') as csvfile111:
reader=csv.reader(csvfile111)
CsvItem=[row for row in reader]
for Item in CsvItem:
if Item[1]==item[0]:
msg.append(Item[3])
writer1.writerow(msg)
#print 'write ok'
break
#print "write ok"
csvfile22.close()
csvfile.close()
csvfile00.close()
代码如下:
#coding=utf-8
#__author__ = 'dehua.li'
from datetime import *
import datetime
import csv
import sys
import time
import string
import os
import os.path
import pylab as plt
def median(lst):
even = (0 if len(lst) % 2 else 1) + 1
half = (len(lst) - 1) / 2
return sum(sorted(lst)[half:half + even]) / float(even)
def mean(lst):
if len(lst)==0:
return 0
return sum(lst)/len(lst)
nightLine="21:01:00"
morningLine="09:01:00"
def getTheDate(date):
[filenamePart1,filenamePart2]=string.split(filename,'.')
[filenamePart11,filenamePart12,filenamePart13]=string.split(filenamePart1,'_')
return filenamePart13
def afterOneMin(time):
[tm_local,ms_local]=string.split(time,'.')
[ymd,hms]=string.split(tm_local,' ')
flag=0
if hms>"21:01:00":
flag=1
elif hms>"09:01:00" and hms<"20:00:00":
flag=1
elif hms>"00:00:00" and hms<"05:00:00":
flag=1
return flag
rootdir="/nethome/dehua.li/orderlifeMyWork/xingzheng/csv"
#csvfileMaxMin = open('e:\dehua.li\csv\__xingzhenMaxMin.csv','wb')
#writer1 = csv.writer(csvfileMaxMin)
#writer1.writerow(['FeedCode','date','SentMaxTime','SentMaxLocalTime','SentMinTime','SentMinLocalTime','SentMeanTime','SentMedian','AckedMaxTime','AckedMaxLocalTime','AckedMinTime','AckedMinLocalTime','AckedMeanTime','AckedMedianTime','Exchange'])
#writer1.writerow(['FeedCode','date','SentMaxTime','SentMinTime','SentMeanTime','SentMedian','AckedMaxTime','AckedMinTime','AckedMeanTime','AckedMedianTime','Exchange'])
msg=[]
codeList=list()
orderList=list()
itemSentList=[]
itemAckedList=[]
feedCode=[]
exchange=[]
zhengshangSentMedian=0
zhengshangSentMean=0
zhengshangAckedMedian=0
zhengshangAckedMean=0
dashangSentMedian=0
dashangSentMean=0
dashangAckedMedian=0
dashangAckedMean=0
shangqiSentMedian=0
shangqiSentMean=0
shangqiAckedMedian=0
shangqiAckedMean=0
zhongjinSentMedian=0
zhongjinSentMean=0
zhongjinAckedMedian=0
zhongjinAckedMean=0
zhengshangSent=[]
zhengshangAcked=[]
dashangSent=[]
dashangAcked=[]
shangqiSent=[]
shangqiAcked=[]
zhongjinSent=[]
zhongjinAcked=[]
zhengshangSentMedianAll=[]
zhengshangSentMeanAll=[]
zhengshangAckedMedianAll=[]
zhengshangAckedMeanAll=[]
dashangSentMedianAll=[]
dashangSentMeanAll=[]
dashangAckedMedianAll=[]
dashangAckedMeanAll=[]
shangqiSentMedianAll=[]
shangqiSentMeanAll=[]
shangqiAckedMedianAll=[]
shangqiAckedMeanAll=[]
zhongjinSentMedianAll=[]
zhongjinSentMeanAll=[]
zhongjinAckedMedianAll=[]
zhongjinAckedMeanAll=[]
zhengshang='0'
dashang='0'
shangqi='0'
zhongjin='0'
with open('/nethome/dehua.li/orderlifeCycleData/heyue_150128.csv','rb') as csvfile:
reader=csv.reader(csvfile)
csvItem=[row for row in reader]
zhengshang=csvItem[300][3]
dashang=csvItem[5][3]
shangqi=csvItem[165][3]
zhongjin=csvItem[435][3]
#for item in csvItem:
# if item[3]==zhengshang:
# print item
for parent,dirname,filenames in os.walk(rootdir):
for filename in filenames:
fileName=os.path.join(rootdir,filename)
csvfile1=open(fileName,'rb')
reader=csv.reader(csvfile1)
CsvItem=[row for row in reader]
for item in CsvItem:
if item[0]=='FeedCode':
continue
if item[0] not in codeList:
codeList.append(item[0])
#print CsvItem[15]
if len(item)<=5:
print fileName
print item
print '++++++++++++++++++++++++++++++'
#if afterOneMin(item[3])==0:
# print item[3]
# continue
if item[5]==zhengshang and item[2]=='Sent':
zhengshangSent.append(int(item[4]))
elif item[5]==zhengshang and item[2]=='Acked':
zhengshangAcked.append(int(item[4]))
elif item[5]==dashang and item[2]=='Sent':
dashangSent.append(int(item[4]))
elif item[5]==dashang and item[2]=='Acked':
dashangAcked.append(int(item[4]))
elif item[5]==shangqi and item[2]=='Sent':
shangqiSent.append(int(item[4]))
if int(item[4])>=600000:
print "------------"
print item
elif item[5]==shangqi and item[2]=='Acked':
shangqiAcked.append(int(item[4]))
elif item[5]==zhongjin and item[2]=='Sent':
zhongjinSent.append(int(item[4]))
elif item[5]==zhongjin and item[2]=='Acked':
zhongjinAcked.append(int(item[4]))
else:
print "wrong info"
print item
if mean(shangqiSent)>420000:
print sum(shangqiSent)
print len(shangqiSent)
print item
print fileName
print shangqiSent
zhengshangSentMedian=median(zhengshangSent)
zhengshangSentMean=mean(zhengshangSent)
zhengshangAckedMedian=median(zhengshangAcked)
zhengshangAckedMean=mean(zhengshangAcked)
dashangSentMedian=median(dashangSent)
dashangSentMean=mean(dashangSent)
dashangAckedMedian=median(dashangAcked)
dashangAckedMean=mean(dashangAcked)
shangqiSentMedian=median(shangqiSent)
shangqiSentMean=mean(shangqiSent)
shangqiAckedMedian=median(shangqiAcked)
shangqiAckedMean=mean(shangqiAcked)
zhongjinSentMedian=median(zhongjinSent)
zhongjinSentMean=mean(zhongjinSent)
zhongjinAckedMedian=median(zhongjinAcked)
zhongjinAckedMean=mean(zhongjinAcked)
#if mean(shangqiSent)>70:
# print '================================'
# print fileName
#print codeList
'''
for listItem in codeList:
itemSentList=[]
itemAckedList=[]
for item in CsvItem:
if item[0]==listItem and item[2]=='Sent':
itemSentList.append(int(item[4]))
exchange=item[5]
elif item[0]==listItem and item[2]=='Acked':
itemAckedList.append(int(item[4]))
#print itemSentList
itemMaxSent=max(itemSentList)
itemMinSent=min(itemSentList)
itemAvgSent=sum(itemSentList)/len(itemSentList)
itemMaxAcked=max(itemAckedList)
itemMinAcked=min(itemAckedList)
itemAvgAcked=sum(itemAckedList)/len(itemAckedList)
SentMedian=median(itemSentList)
AckedMedian=median(itemAckedList)
msg=[]
msg.append(listItem) #0
msg.append("2015/01/14") #1
msg.append(itemMaxSent) #2
msg.append(itemMinSent) #3
msg.append(itemAvgSent) #4
msg.append(SentMedian) #5
msg.append(itemMaxAcked) #6
msg.append(itemMinAcked) #7
msg.append(itemAvgAcked) #8
msg.append(AckedMedian) #9
msg.append(exchange) #10
if len(msg)>15:
print "------------------------------"
print msg
writer1.writerow(msg)
'''
zhengshangSentMedianAll.append(zhengshangSentMedian)
zhengshangSentMeanAll.append(zhengshangSentMean)
zhengshangAckedMedianAll.append(zhengshangAckedMedian)
zhengshangAckedMeanAll.append(zhengshangAckedMean)
dashangSentMedianAll.append(dashangSentMedian)
dashangSentMeanAll.append(dashangSentMean)
dashangAckedMedianAll.append(dashangAckedMedian)
dashangAckedMeanAll.append(dashangAckedMean)
shangqiSentMedianAll.append(shangqiSentMedian)
shangqiSentMeanAll.append(shangqiSentMean)
shangqiAckedMedianAll.append(shangqiAckedMedian)
shangqiAckedMeanAll.append(shangqiAckedMean)
zhongjinSentMedianAll.append(zhongjinSentMedian)
zhongjinSentMeanAll.append(zhongjinSentMean)
zhongjinAckedMedianAll.append(zhongjinAckedMedian)
zhongjinAckedMeanAll.append(zhongjinAckedMean)
plt.figure(1)
plt.figure(2)
plt.figure(3)
plt.figure(4)
plt.figure(1)
plt.title('SentMean r-zhengshang b-dashang,green-shangqi grey-zhongjin')
plt.plot(range(1,len(zhengshangSentMeanAll)+1),zhengshangSentMeanAll,'r')
plt.plot(range(1,len(dashangSentMeanAll)+1),dashangSentMeanAll,'b')
plt.plot(range(1,len(shangqiSentMeanAll)+1),shangqiSentMeanAll,'g')
plt.plot(range(1,len(zhongjinSentMeanAll)+1),zhongjinSentMeanAll,'grey')
plt.savefig('/nethome/dehua.li/orderlifeMyWork/xingzheng/data_noTPO_in10minutes/SentMean.png')
plt.figure(2)
plt.title('SentMedian r-zhengshang b-dashang,green-shangqi grey-zhongjin')
plt.plot(range(1,len(zhengshangSentMedianAll)+1),zhengshangSentMedianAll,'r')
plt.plot(range(1,len(dashangSentMedianAll)+1),dashangSentMedianAll,'b')
plt.plot(range(1,len(shangqiSentMedianAll)+1),shangqiSentMedianAll,'g')
plt.plot(range(1,len(zhongjinSentMedianAll)+1),zhongjinSentMedianAll,'grey')
plt.savefig('/nethome/dehua.li/orderlifeMyWork/xingzheng/data_noTPO_in10minutes/SentMedian.png')
plt.figure(3)
plt.title('AckedMean r-zhengshang b-dashang,green-shangqi grey-zhongjin')
plt.plot(range(1,len(zhengshangAckedMeanAll)+1),zhengshangAckedMeanAll,'r')
plt.plot(range(1,len(dashangAckedMeanAll)+1),dashangAckedMeanAll,'b')
plt.plot(range(1,len(shangqiAckedMeanAll)+1),shangqiAckedMeanAll,'g')
plt.plot(range(1,len(zhongjinAckedMeanAll)+1),zhongjinAckedMeanAll,'grey')
plt.savefig('/nethome/dehua.li/orderlifeMyWork/xingzheng/data_noTPO_in10minutes/AckedMean.png')
plt.figure(4)
plt.title('AckedMedian r-zhengshang b-dashang,green-shangqi grey-zhongjin')
plt.plot(range(1,len(zhengshangAckedMedianAll)+1),zhengshangAckedMedianAll,'r')
plt.plot(range(1,len(dashangAckedMedianAll)+1),dashangAckedMedianAll,'b')
plt.plot(range(1,len(shangqiAckedMedianAll)+1),shangqiAckedMedianAll,'g')
plt.plot(range(1,len(zhongjinAckedMedianAll)+1),zhongjinAckedMedianAll,'grey')
plt.savefig('/nethome/dehua.li/orderlifeMyWork/xingzheng/data_noTPO_in10minutes/AckedMedian.png')
plt.show()
print 'over'
希望本文所述对大家的Python程序设计有所帮助。
数据分析咨询请扫描二维码
若不方便扫码,搜微信号:CDAshujufenxi
机器学习算法工程的核心价值,在于将理论算法转化为可落地、可复用、高可靠的工程化解决方案,解决实际业务中的痛点问题。不同于 ...
2026-03-18在动态系统状态估计与目标跟踪领域,高精度、高鲁棒性的状态感知是机器人导航、自动驾驶、工业控制、目标检测等场景的核心需求。 ...
2026-03-18“垃圾数据进,垃圾结果出”,这是数据分析领域的黄金法则,更是CDA(Certified Data Analyst)数据分析师日常工作中时刻恪守的 ...
2026-03-18在机器学习建模中,决策树模型因其结构直观、易于理解、无需复杂数据预处理等优势,成为分类与回归任务的首选工具之一。而变量重 ...
2026-03-17在数据分析中,卡方检验是一类基于卡方分布的假设检验方法,核心用于分析分类变量之间的关联关系或实际观测分布与理论期望分布的 ...
2026-03-17在数字化转型的浪潮中,企业积累的数据日益庞大且分散——用户数据散落在注册系统、APP日志、客服记录中,订单数据分散在交易平 ...
2026-03-17在数字化时代,数据分析已成为企业决策、业务优化、增长突破的核心支撑,从数据仓库搭建(如维度表与事实表的设计)、数据采集清 ...
2026-03-16在数据仓库建设、数据分析(尤其是用户行为分析、业务指标分析)的实践中,维度表与事实表是两大核心组件,二者相互依存、缺一不 ...
2026-03-16数据是CDA(Certified Data Analyst)数据分析师开展一切工作的核心载体,而数据读取作为数据生命周期的关键环节,是连接原始数 ...
2026-03-16在用户行为分析实践中,很多从业者会陷入一个核心误区:过度关注“当前数据的分析结果”,却忽视了结果的“泛化能力”——即分析 ...
2026-03-13在数字经济时代,用户的每一次点击、浏览、停留、转化,都在传递着真实的需求信号。用户行为分析,本质上是通过收集、整理、挖掘 ...
2026-03-13在金融、零售、互联网等数据密集型行业,量化策略已成为企业挖掘商业价值、提升决策效率、控制经营风险的核心工具。而CDA(Certi ...
2026-03-13在机器学习建模体系中,随机森林作为集成学习的经典算法,凭借高精度、抗过拟合、适配多场景、可解释性强的核心优势,成为分类、 ...
2026-03-12在机器学习建模过程中,“哪些特征对预测结果影响最大?”“如何筛选核心特征、剔除冗余信息?”是从业者最常面临的核心问题。随 ...
2026-03-12在数字化转型深度渗透的今天,企业管理已从“经验驱动”全面转向“数据驱动”,数据思维成为企业高质量发展的核心竞争力,而CDA ...
2026-03-12在数字经济飞速发展的今天,数据分析已从“辅助工具”升级为“核心竞争力”,渗透到商业、科技、民生、金融等各个领域。无论是全 ...
2026-03-11上市公司财务报表是反映企业经营状况、盈利能力、偿债能力的核心数据载体,是投资者决策、研究者分析、从业者复盘的重要依据。16 ...
2026-03-11数字化浪潮下,数据已成为企业生存发展的核心资产,而数据思维,正是CDA(Certified Data Analyst)数据分析师解锁数据价值、赋 ...
2026-03-11线性回归是数据分析中最常用的预测与关联分析方法,广泛应用于销售额预测、风险评估、趋势分析等场景(如前文销售额预测中的多元 ...
2026-03-10在SQL Server安装与配置的实操中,“服务名无效”是最令初学者头疼的高频问题之一。无论是在命令行执行net start启动服务、通过S ...
2026-03-10