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Learn how to resolve pandas corrupt file errors when appending data to an existing Excel file using Python. Clear guidelines and code snippets provided.
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Resolving pandas Corrupt File Error When Appending to Excel in Python

Working with Excel files is a common task in data manipulation, especially when using the pandas library in Python. However, encountering errors can be frustrating, particularly when these errors involve file corruption after appending data. This guide will guide you through resolving a specific issue where trying to append data to an existing Excel file in Python using pandas results in a Bad CRC-32 error. Read on to find a step-by-step solution!

Understanding the Problem

The error arises when a user attempts to append data to an Excel file using the ExcelWriter object from the pandas library. The provided code attempts to append a newly scraped list of items to a specific sheet in an Excel workbook. However, by doing so, it encounters a corrupt file error even though the new data is being fetched correctly with the Scrapy framework.

Here's a summarized version of what the original attempt included:

Extraction of data from a web page using Scrapy.

Using pd.ExcelWriter to append this data to an existing Excel file.

An attempt to calculate the last row of data for proper insertion of new entries.

Dissecting the Code Issues

The primary issues leading to the error in the provided code include:

Incorrect Reading of the Existing Excel File: The code attempts to create a DataFrame directly from the path of the Excel file (df_last=pd.DataFrame('output_res.xlsx')), which is incorrect and likely triggers the corrupt file error.

Last Row Calculation: The calculation for the last row (lastRow=df_last['plate'].iget(-1)) directly refers to the last row without appropriate context and assignment. Moreover, due to the earlier issue, this value is likely unassigned.

Step-by-Step Solution

To resolve these issues, we can refactor the code to work correctly when appending data to the Excel file. Follow these steps to correct the code:

Step 1: Define itemList Globally

Move the itemList variable outside the class definition to maintain its state across multiple calls:

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

Step 2: Correctly Read the Existing Excel File

Instead of using pd.DataFrame with the file name directly, you can read the Excel file into a DataFrame properly using pd.read_excel():

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

Step 3: Append Data Correctly Without Last Row Calculation

Since we now have access to the existing data in the DataFrame, we can directly append new data without needing to calculate the last row specifically:

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

Full Revised parse Method Example

Here is how the final parse method would look after incorporating the above fixes:

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

Conclusion

By following the steps outlined above, you should be able to fix the pandas corrupt file error when appending data to an Excel file. With more careful control over reading and writing operations, you can effectively manage data storage in your applications without encountering file corruption.

Feel free to reach out if you have further questions or run into other issues while working with pandas and Excel!