Automate Word Table Extraction to Excel with Python: A Step-by-Step Guide

In this tutorial we show how to extract specific fields (date, title, document number) from hundreds of similarly formatted tables in a Word document and store them into an Excel spreadsheet.

First we import the required libraries:

# import needed libraries
from docx import Document
import datetime
from openpyxl import Workbook

We load the Word file, iterate over all tables, and for each entry (which occupies three rows) we retrieve the date, title, and document number. The date strings are originally in "day/month" format and are converted to "YYYY-MM-DD" using datetime.datetime.strptime and strftime. Empty dates are replaced with "-".

Example extraction loop:

# example loop
n = 0
for j in range(len(tables)):
    for i in range(0, len(tables[j].rows)+1, 3):
        try:
            date = tables[j].cell(i, 1).text
            if '/' in date:
                date = datetime.datetime.strptime(date, '%d/%m').strftime('2020-%m-%d')
            else:
                date = '-'
            title = tables[j].cell(i+1, 1).text.strip()
            dfn = tables[j].cell(i, 3).text.strip()
            n += 1
            row = [n, date, ' ', title, dfn, ' ']
            sheet.append(row)
        except Exception as error:
            print(error)
            continue

After processing all tables we create an Excel workbook with headers

['序号','收文时间','办文编号','文件标题','文号','备注']

and append each extracted row. Finally we save the workbook to a file.

# create workbook and save
wb = Workbook()
sheet = wb.active
header = ['序号','收文时间','办文编号','文件标题','文号','备注']
sheet.append(header)
# ... (append rows in the loop above)
wb.save(r'C:\Users\20200420.xlsx')