In daily office work, you often encounter the need to extract table content from Word documents and write it to Excel tables. By using the Python programming language, we can accomplish this task efficiently. This article will provide a complete code example in detail how to use Python to extract the content of Word document tables and write them to Excel.
1. Environmental preparation
Before we start writing code, we need to install some Python libraries to handle Word and Excel documents. The main libraries used are python-docx and openpyxl.
1. Install the python-docx library
The python-docx library is used to read and manipulate Word documents. Install using the following command:
pip install python-docx
2. Install the openpyxl library
The openpyxl library is used to read and write Excel files. Install using the following command:
pip install openpyxl
2. Read tables in Word documents
First, you need to write code to read the table contents in Word documents. Here is a sample code for extracting all table contents from Word documents and printing them out.
Sample code:
from docx import Document
def read_word_tables(file_path):
doc = Document(file_path)
tables =
data = []
for table in tables:
table_data = []
for row in :
row_data = []
for cell in :
row_data.append()
table_data.append(row_data)
(table_data)
return data
# Example usageword_file = ''
tables = read_word_tables(word_file)
for i, table in enumerate(tables):
print(f"Table {i+1}:")
for row in table:
print("\t".join(row))In this example, the read_word_tables function accepts the path to a Word file and returns a list of all table contents. Each table content is stored in the form of a two-dimensional list, where each sublist represents a row and the elements in each sublist represent the content of a cell.
3. Write the table content to Excel
Write the extracted table contents to the Excel file. Here is a sample code for writing table contents to an Excel file.
Sample code:
from openpyxl import Workbook
def write_to_excel(file_path, tables):
wb = Workbook()
ws =
for table in tables:
for row in table:
(row)
([]) # Add an empty row to separate different tables
(file_path)
# Example usageexcel_file = ''
write_to_excel(excel_file, tables)
In this example, the write_to_excel function accepts an Excel file's path and table content list and writes the table content to the Excel file. Create a new workbook using the Workbook object of the openpyxl library and add each row of data to the worksheet by method.
4. Complete example: Extract tables from Word and write them to Excel
Combining the above steps, write a complete sample code that extracts table content from a Word document and writes it to an Excel file.
Sample code:
from docx import Document
from openpyxl import Workbook
def read_word_tables(file_path):
doc = Document(file_path)
tables =
data = []
for table in tables:
table_data = []
for row in :
row_data = []
for cell in :
row_data.append()
table_data.append(row_data)
(table_data)
return data
def write_to_excel(file_path, tables):
wb = Workbook()
ws =
for table in tables:
for row in table:
(row)
([]) # Add an empty row to separate different tables
(file_path)
# Example usageword_file = ''
excel_file = ''
tables = read_word_tables(word_file)
write_to_excel(excel_file, tables)
print(f"SuccessfullyWordExtract and write table contents in the documentExceldocument：{excel_file}")
Considerations in practical applications
In practical applications, you may encounter some special situations and problems when processing Word documents and Excel files.
1. Handle complex tables
Tables in Word documents may have complex structures such as merged cells, nested tables, etc. When dealing with these complex tables, additional code logic is required to handle these special cases.
2. Table data cleaning
Tabular data extracted from Word documents may contain some extra spaces or line breaks. Before writing to Excel, the data can be cleaned to ensure clean and consistent data.
3. Large file processing
Memory and performance issues may need to be considered for large Word documents with large amounts of tables or Excel files that require large amounts of data to be written. Large files can be processed by batch reading and writing.
Sample code:
import re
from docx import Document
from openpyxl import Workbook
def clean_text(text):
# Remove excess spaces and line breaks return (r'\s+', ' ', text).strip()
def read_word_tables(file_path):
doc = Document(file_path)
tables =
data = []
for table in tables:
table_data = []
for row in :
row_data = []
for cell in :
row_data.append(clean_text())
table_data.append(row_data)
(table_data)
return data
def write_to_excel(file_path, tables):
wb = Workbook()
ws =
for table in tables:
for row in table:
(row)
([]) # Add an empty row to separate different tables
(file_path)
# Example usageword_file = ''
excel_file = ''
tables = read_word_tables(word_file)
write_to_excel(excel_file, tables)
print(f"SuccessfullyWordExtract and write table contents in the documentExceldocument：{excel_file}")
Summarize
This article details how to use Python to extract table content from a Word document and write to an Excel file. By using the python-docx library to read Word documents and the openpyxl library to write to Excel files, we can complete this task efficiently. In addition, this article also introduces some considerations and solutions in practical applications.
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