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我正在将 ascii 文件中的数据读取到数组中，并将数据写入 excel 文件以进行进一步的后处理。总共有 337 列和 1100 行——这使得 xlsx 中有 370700 个单元格。

写入 excel 数据文件需要很长时间——在 16 GB 机器上大约需要 25-35 分钟。

有没有其他方法可以更有效地在 excel 文件中写入数据？

任何帮助都将不胜感激。

import numpy as np 
import win32com.client as win32 
import matplotlib.pyplot as plt 
from win32com import client  from time
clock, time  start_time = clock()

itr = int(raw_input('Enter number of iteration = '))
f1 =open("Case_AT-6_WF_fl2.gid","r")

s2 = f1.read() 
a = s2.split() 

count=0 for col in open("Case_AT-6_WF_fl2.gid",'r'):
count = count+1 column = int(len(col.split()))
sm = int(itr * column)

digit = map(float,(a[(len(a)-sm):l
a[(column+7):(column*2+7)]

# preparing 2D matrix dig = np.array(digit)  dig1 =(dig.reshape

### *******Plotting
## print name

for i in range(len(name)):    
    print i,"=",name[i]

plot = int(raw_input("\nEnter variable number for plot =" ))

# writing Excel file*******************************************

print('file printing option: 1 = Yes 2= No') q = int(raw_input(
printing option = "))

if q==1 :
    excel = win32.gencache.EnsureDispatch('Excel.Application')
    excel.Visible = False
    wb = excel.Workbooks.Add()
    ws=wb.Sheets(1)
    ws.Name = "MyData"
    ws.Activate
    for kk in range(len(name)):
        ws.Cells(2,kk+1).Value = name[kk]
        ws.Cells(3,kk+1).Value = unit[kk]
m = 0
k =0
for j in range(itr):
    for k in range(column):
        ws.Cells(j+5,k+1).Value=dig1[j][k]
        m = m+1
       print '',m
print clock() - start_time, "seconds"

wb.SaveAs('C:\\Documents andSettings\\sd47086\\Desktop\\test\\MyWorkbook3.xlsx')
excel.Application.Quit()
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1 回答 1

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分配范围通常比单独设置每个单元格要快得多。您只需确保 python 序列与范围的大小匹配，例如 ws.Range('A1:B10000').Value = ('a','b') * 10000

于 2012-07-22T05:49:41.017 回答