转换表列出在Excel

Question

我有许多优于其中数据被布置在片材表如下所示

我想，如下所示各该表的转换为另一种类似列表的格式。

在该表中：

Dir -> Name of the tab 
Year -> Same for entire table 
DOM -> Day of the month 
DOW -> Day of the week. 
Hour -> Column label in original table 
Traffic Count -> Value in the original table 

有接近1000个这种片材。每张表中的数据位于相同的位置。做这个的最好方式是什么？我应该写一个VBA脚本还是Excel中有任何东西可以用来让我的生活更轻松？

Answer 1

我解决了使用python和xlrd模块

import xlrd 
import numpy as np 
from os import listdir, chdir 
import calendar 
import re 

direction = {'N':0,'S':1,'E':2,'W':3} 
rend = [0, 40, 37, 40, 39, 40, 39, 40, 40, 39, 40, 39, 40] 

# Initialize the matrix to store final result 
aData = np.matrix(np.zeros((0,7))) 

# get all the xlsx files from the directory. 
filenames = [ f for f in listdir('.') if f.endswith('.xlsx') ] 

# for each .xlsx in the current directory 
for file in filenames: 
    # The file names are in the format gdot_39446_yyyy_mm.xlsx 
    # yyyy is the year and mm is the month number with 0 -Jan and 11 - Dec 
    # I extracted the month and year info from the file name 

    ms = re.search('.+_.+_.+_([0-9]+)\.',file,re.M).group(1) 
    month = int(ms) + 1 
    year = int(file[11:15]) 

    # open the workbook 
    workbook = xlrd.open_workbook(file) 

    # the workbook has three sheets. I want information from 
    # sheet2 and sheet3 (indexed by 1 adn 2 resp.) 
    for i in range(1,3): 
     sheet = workbook.sheet_by_index(i) 
     di = sheet.name[-1] 
     data = [[sheet.cell_value(r,c) for c in range(2,26)] for r in range(9,rend[month])] 

     mData = np.matrix(data) 
     mData[np.where(mData=='')] = 0 # some cells are blank. Insert 0 in those cells 
     n,d = mData.shape 
     rows = n * d 

     rData = np.matrix(np.zeros((rows,7))) 
     rData[:,0].fill(direction[di]) 
     rData[:,1].fill(year) 
     rData[:,2].fill(month) 
     for i in range(rows): 
      rData[i,3] = (i/24) + 1 
      rData[i,4] = calendar.weekday(year,month,(i/24) + 1) 
      rData[i,5] = i%24 

     for i in range(n): 
      rData[i*24:((i+1)*24),6] = mData[i,:].T 

     aData = np.vstack((aData,rData)) 

    np.savetxt("alldata.csv",aData, delimiter=',', fmt='%s')