我正在尝试将Excel.xlsx文件解析为csv文件。这是Excel文件:
Date Person 1 Person 2
02/03/2015 Bob James A
03/03/2015 Billy Nic
04/03/2015 Sally Mark
05/03/2015 Alan James A
06/03/2015 James W James A
我的Python脚本:
import xlrd
import csv
book = xlrd.open_workbook('rota.xlsx')
sheet = book.sheet_by_name('Sheet1')
csvfile = open('output.csv', 'wb')
wr = csv.writer(csvfile, quoting=csv.QUOTE_ALL)
for rownum in range(sheet.nrows):
wr.writerow(sheet.row_values(rownum))
csvfile.close()
然而它会输出这样的日期:
Date,Person1,Person2
41884,Bob,James B
41885,Billy,Nic
41886,Sally,Mark
41887,Alan,James A
41888,James W,James A
我知道xldate_as_tuple函数或类似的东西将输出转换为有意义的值,但我无法弄清楚如何使用它。 任何帮助我都会非常感激。
答案 0 :(得分:3)
以下是一种可能的解决方案:
import xlrd
import csv
from datetime import datetime
book = xlrd.open_workbook('rota.xlsx')
sheet = book.sheet_by_name('Sheet1')
csvfile = open('output5.csv', 'wb')
wr = csv.writer(csvfile, quoting=csv.QUOTE_ALL)
wr.writerow(sheet.row_values(0))
for rownum in range(1,sheet.nrows):
year, month, day, hour, minute, sec = xlrd.xldate_as_tuple(int(sheet.row_values(rownum)[0]), book.datemode)
py_date = datetime(year, month, day, hour, minute)
wr.writerow([py_date] + sheet.row_values(rownum)[1:])
csvfile.close()
输出:
"Date "," Person 1","Person 2"
"2015-02-03 00:00:00"," Bob ","James A "
"2015-03-03 00:00:00"," Billy ","Nic "
"2015-04-03 00:00:00"," Sally ","Mark "
"2015-05-03 00:00:00"," Alan ","James A "
"2015-06-03 00:00:00","James W ","James A "
版本2:
代码:
#! /usr/bin/python
import xlrd
import csv
from datetime import datetime
book = xlrd.open_workbook('rota.xlsx')
sheet = book.sheet_by_name('Sheet1')
csvfile = open('output5.csv', 'wb')
wr = csv.writer(csvfile, quoting=csv.QUOTE_ALL)
for rownum in range(sheet.nrows):
date = sheet.row_values(rownum)[0]
if isinstance( date, float) or isinstance( date, int ):
year, month, day, hour, minute, sec = xlrd.xldate_as_tuple(date, book.datemode)
py_date = "%02d/%02d/%04d" % (month, day,year)
wr.writerow([py_date] + sheet.row_values(rownum)[1:])
else:
wr.writerow(sheet.row_values(rownum))
csvfile.close()
输出:
"Date "," Person 1","Person 2"
"02/03/2015"," Bob ","James A "
"03/03/2015"," Billy ","Nic "
"04/03/2015"," Sally ","Mark "
"05/03/2015"," Alan ","James A "
"06/03/2015","James W ","James A "