How to Prevent Overwriting Data in Excel with Python using xlsxwriter

Learn how to extract data from multiple Word tables and write them into a single Excel sheet without overwriting the content. This guide will show you the correct way to append data using Python.
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How to Prevent Overwriting Data in Excel with Python using xlsxwriter

When working with data extraction, specifically from Word tables to Excel, one common problem arises: overwriting existing content in your Excel file. If you’ve encountered an issue where only the last loop’s data remains in your Excel sheet, you’re not alone. Let’s look at a practical approach to solve this problem using Python’s pandas and xlsxwriter libraries.

The Problem

Imagine you have several Word documents, each containing valuable tabular data. Your goal is to extract specific rows from these tables and consolidate them into a single Excel sheet. However, upon execution, you find that your Excel file only contains the data from the last file processed. This occurs because you are writing to the Excel sheet in a way that overwrites previous entries.

Understanding the Solution

To correctly append data into Excel without losing previously written rows, you can modify your code to gather all data first before saving it to the sheet. Here’s how to do it step by step:

1. Set Up Your Environment

Start by importing the required libraries and setting your document path:

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2. Collect Data From Word Files

Next, create a list to hold your Word documents and loop through each file in the specified folder.

[[See Video to Reveal this Text or Code Snippet]]

This code snippet retrieves all Word documents from a folder and stores them in the worddocs_list for processing.

3. Extract Data from Tables

Instead of directly writing to Excel within the inner loop, first gather the data from the Word tables into a list:

[[See Video to Reveal this Text or Code Snippet]]

This line effectively extracts the specified data from each table. It pulls data from the rows and cells you need, creating a list of lists.

4. Write Data to Excel

Once you have all your data collected in out_rows, create a DataFrame and write it to Excel in one go. This avoids overwriting issues and keeps all your collected data intact:

[[See Video to Reveal this Text or Code Snippet]]

Here, the DataFrame df is constructed from out_rows, and then it’s written to the Excel file with a single command, preserving all previously entered data.

Conclusion

By gathering all required data before writing it to Excel, you can maintain the integrity of your dataset and prevent overwriting issues. Using pandas and xlsxwriter together allows for efficient handling of Excel write operations, even when dealing with multiple inputs, such as figures from various Word documents.

With these steps, your consolidated data should now appear correctly in Excel, free from overwriting concerns. Happy coding!