python pandas 对时间序列文件处理代码

import pandas as pdfrom numpy import *import matplotlib.pylab as pltimport  copydef read(filename):    dat=pd.read_csv(filename,iterator=True)    loop = True    chunkSize = 1000000    R=[]    while loop:        try:            data = dat.get_chunk(chunkSize)            data=data.loc[:,'B':'C']   #   切片            data=data[data.B==855]     #条件选择            data['C']=pd.to_datetime(data['C'])  #  转换成时间格式            data=data.set_index(['C'])              #  设置索引            data.loc[:,'D']=array([1]*len(data))   #增加一列            data=data.resample('D').sum()  #按天求和            data=data.loc[:,'D']  #截取            data.fillna(0)   #填充缺失值            R.append(data)        except StopIteration:            loop = False            PRint ("Iteration is stopped.")    R.to_csv('855_pay.csv') # 保存def read2(filename):    reader=pd.read_csv(filename,iterator=True)    loop = True    chunkSize = 100000    chunks = []    while loop:        try:           chunk = reader.get_chunk(chunkSize)           chunks.append(chunk)        except StopIteration:           loop = False           print ("Iteration is stopped.")    df = pd.concat(chunks, ignore_index=True)    return dfdef read3save(filename):    dat=pd.read_csv(filename)    #data = dat.get_chunk(chunkSize)    data=dat.loc[:,'B':'C']   #   切片    data=data[data.B==855]#条件选择    print(shape(data))    data['C']=pd.to_datetime(data['C'])  #  转换成时间格式    data=data.set_index(['C'])#  设置索引    if len(data)==0:        return    data.loc[:,'D']=array([1]*len(data))   #增加一列    data=data.resample('D').sum()  #按天求和    data=data.loc[:,'D']  #截取    data.fillna(0)   #填充缺失值    data.to_csv('855_pay.csv',mode='a') # 保存def loadDataSet(fileName, delim='/t'):    fr = open(fileName)    stringArr = [line.strip().split(delim) for line in fr.readlines()]    datArr = [list(map(float,line)) for line in stringArr]    return mat(datArr)def  getShopData():    fr = open('shopInfo.txt')    shopID = [line.strip().split('/n') for line in fr.readlines()]   # datArr = [list(map(float,line))for line in stringArr]    for  i in range(1,9):      name="user_pay.001.00%d"%i      dat=pd.read_csv(name)      #data = dat.get_chunk(chunkSize)      data=dat.loc[:,'B':'C']   #   切片      for factor in shopID:          data=data[data.B==int(str(factor[0]))]#条件选择          print(shape(data))          if len(data)==0: continue          data['C']=pd.to_datetime(data['C'])  #  转换成时间格式          data=data.set_index(['C'])#  设置索引          data.loc[:,'D']=array([1]*len(data))   #增加一列          data=data.resample('D').sum()  #按天求和          data=data.loc[:,'D']  #截取          data.fillna(0)   #填充缺失值          s=str(factor[0])          savename='D:/python/data/%s_pay.csv'%s          data.to_csv(savename,mode='a') # 保存          del dat    print("over")def tset(filename):    dat=pd.read_csv(filename)    #data = dat.get_chunk(chunkSize)    data=dat.loc[:,'B':'C']   #   切片    data=data[data.B==855]#条件选择    print(shape(data))    data['C']=pd.to_datetime(data['C'])  #  转换成时间格式    data=data.set_index(['C'])#  设置索引    if len(data)==0:        return    data.loc[:,'D']=array([1]*len(data))   #增加一列    data=data.resample('D').sum()  #按天求和    data=data.loc[:,'D']  #截取    data.fillna(0)   #填充缺失值    #data.to_csv('855_pay.csv',mode='a') # 保存    s='my'    savename='D:/python/data/%s_pay.csv'%s    data.to_csv(savename,mode='a') # 保存     def  getShopData2(filename):      import csv    #  fr = open('shopInfo.txt')     # shopID = [line.strip().split('/n') for line in fr.readlines()]   # datArr = [list(map(float,line))for line in stringArr]    #for  i in range(1,9):    #name="user_pay.001.00%d"%i      dat=pd.read_csv(filename)      #data = dat.get_chunk(chunkSize)      data=dat.loc[:,'B':'C'] #   切片      data['C']=pd.to_datetime(data['C'])  #  转换成时间格式      data=data.set_index(['C'])#  设置索引      data.loc[:,'D']=array([1]*len(data))   #增加一列      for i in range(1,2001):          d=copy.copy(data)          d=d[data.B==i]#条件选择          #print(shape(d))          print(i)          if len(d)==0: continue          d=d.resample('D').sum()  #按天求和          d=d.loc[:,'D']  #截取          d.fillna(0)   #填充缺失值          s=str(i)          #print(s)          savename='D:/python/data2/%s_pay.csv'%s          c=open(savename,'a')          writer=csv.writer(c)          writer.writerow(['C','D'])          c.close()          d.to_csv(savename,mode='a') # 保存         # del dat          print("over")def formatData():     #fr = open('shopInfo.txt')     #shopID = [line.strip().split('/n') for line in fr.readlines()]   # datArr = [list(map(float,line))for line in stringArr]      #data = dat.get_chunk(chunkSize)     for i in range(1,2001):          s=str(i)          print(s)          name='D:/python/data2/%s_pay.csv'%s          dat=pd.read_csv(name)          data['C']=pd.to_datetime(data['C'])  #  转换成时间格式          data=data.set_index(['C'])#  设置索引          data=data.resample('D').sum()  #按天求和          data.fillna(0)   #填充缺失值          savename='D:/python/data3/%s_pay.csv'%s          data.to_csv(savename,mode='w') # 保存          del dat          print("over")