SoFunction
Updated on 2025-03-04

Code implementation for quickly converting Excel into HTML using Python

1. Choose the right tools and libraries

In Python, there are a variety of libraries that can be used to process Excel files, among which pandas and openpyxl are the two most commonly used libraries. pandas provides powerful data processing and analysis capabilities, and supports exporting DataFrame objects to HTML format. openpyxl focuses on reading and writing operations of Excel files. Although it does not directly support HTML format export, you can read the data in Excel files and then use other methods to convert it into HTML.

However, in order to simplify operations and improve efficiency, this article will mainly use the pandas library to complete the Excel to HTML conversion. Pandas is not only easy to use, but also powerful, and can meet most data processing needs.

2. Install the necessary libraries

Before starting，You need to make sure it is installedpandasandopenpyxl（AlthoughopenpyxlNot required，But if you need to deal with it.xlsxFormatExceldocument，It will be very useful）。 You can use the pip command to install these libraries:

pip install pandas openpyxl

3. Read Excel files

First, you need to use pandas' read_excel function to read Excel files. This function supports multiple parameters, allowing you to specify the worksheet, column, row, etc. to be read. Here is a simple example:

import pandas as pd
 
# Read Excel filedf = pd.read_excel('', sheet_name='Sheet1')
 
# Print the first few lines of data to verify that the read is successfulprint(())

In this example, we read an Excel file named and specify the worksheet name Sheet1. We then printed the first few lines of data using the head method to verify that the read was successful.

4. Convert DataFrame to HTML

Once you have successfully read the Excel file and store it in a DataFrame object, you can convert it to HTML format using the to_html method of DataFrame. This method provides a variety of parameters, allowing you to customize the style, column names, indexes, etc. of HTML tables.

Here is an example of converting a DataFrame to HTML:

# Convert DataFrame to HTMLhtml_table = df.to_html(index=False, border=0, classes='table table-striped')
 
# Print HTML tableprint(html_table)

In this example, we use the to_html method and specify the following parameters:

index=False: Do not output the index of DataFrame as a column of the HTML table.
border=0: Set the border width of the HTML table to 0 (you can adjust this value as needed).
classes='table table-striped': Add Bootstrap' CSS class to HTML tables to achieve better styles (this requires that your webpage already contains the Bootstrap CSS file).

5. Save HTML files

If you want to save the generated HTML table to a file, you can do this using Python's file manipulation function. Here is an example:

# Save HTML table to filewith open('', 'w', encoding='utf-8') as file:
    ('<!DOCTYPE html>\n<html lang="en">\n<head>\n')
    ('<meta charset="UTF-8">\n<meta name="viewport" content="width=device-width, initial-scale=1.0">\n')
    ('<link rel="stylesheet" href="/bootstrap/4.5.2/css/">\n')
    ('<title>Excel to HTML</title>\n</head>\n<body>\n')
    ('<div class="container">\n')
    ('<h1>Excel Data as HTML Table</h1>\n')
    (html_table)  # Write to HTML table    ('</div>\n</body>\n</html>

In this example, we create a file named and write the header of the HTML document, the CSS link of Bootstrap, and a container containing the HTML table. Note that we used Bootstrap's CDN link to load CSS styles for better visual effects.

6. Complete examples and cases

Here is a complete example showing how to convert an Excel file to an HTML file, with a simple case:

import pandas as pd
 
# Read Excel filedf = pd.read_excel('', sheet_name='Sheet1')
 
# Convert DataFrame to HTMLhtml_table = df.to_html(index=False, border=1, classes='table table-striped')
 
# Save HTML table to filewith open('', 'w', encoding='utf-8') as file:
    ('<!DOCTYPE html>\n<html lang="en">\n<head>\n')
    ('<meta charset="UTF-8">\n<meta name="viewport" content="width=device-width, initial-scale=1.0">\n')
    ('<link rel="stylesheet" href="/bootstrap/4.5.2/css/">\n')
    ('<title>Excel to HTML Example</title>\n</head>\n<body>\n')
    ('<div class="container mt-5">\n')
    ('<h1>Excel Data Converted to HTML Table</h1>\n')
    (html_table)  # Write to HTML table    ('</div>\n</body>\n</html>
print("HTML file has been generated successfully!")

Case description:

  • Excel file: We have an Excel file called that contains a worksheet called Sheet1.
  • Read and Convert: We use pandas to read Excel files and convert them to HTML tables.
  • Save HTML file: We save the generated HTML table to a file named and include the CSS style of Bootstrap for better visual effects.
  • Result verification: You can open the file in your browser to see if the generated HTML table meets expectations.

7. Precautions and FAQs

  • Excel file format: Make sure your Excel file is in .xlsx or .xls format. If the file is in another format (such as .csv), you need to use another method to read it.
  • Character encoding: When saving HTML files, make sure to use the correct character encoding (such as utf-8) to avoid garbled problems.
  • Dependencies: Make sure that the pandas and openpyxl libraries are installed in your Python environment. If not installed, please follow the previous steps to install.
  • Style customization: You can customize the style of HTML tables as needed. For example, you can modify the parameters of the to_html method to adjust the properties of the table's borders, fonts, colors, etc.; you can also add custom CSS styles to the HTML file to achieve more complex visual effects.

8. Summary

This article describes how to quickly convert Excel files into HTML format using Python. We can easily implement this transformation process by using the read_excel function in the pandas library and the to_html method of the DataFrame object. At the same time, we also provide a complete example and case to demonstrate how to read Excel files, convert data and save them as HTML files. I hope these contents can help you better handle data conversion tasks between Excel and HTML.

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