


How Can I Use Pandas to Write to an Excel File Without Overwriting Existing Data?
Handling Excel Overwrites with Pandas
Pandas provides a robust option for writing to Excel files, but an issue arises when writing to an existing file without overwriting its contents. By default, pandas.ExcelWriter overrides existing data when creating sheets.
Example and Problem
Consider the following code:
import pandas as pd writer = pd.ExcelWriter('Masterfile.xlsx') data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2']) writer.save()
In this scenario, "Masterfile.xlsx" has pre-existing tabs. When this code executes, a new "Main" sheet is created and populated, but all other tabs are erased.
Solution
To prevent data loss, Pandas employs the openpyxl library for working with XLSX files. Here's an enhanced version of the code:
import pandas as pd from openpyxl import load_workbook book = load_workbook('Masterfile.xlsx') writer = pd.ExcelWriter('Masterfile.xlsx', engine='openpyxl') writer.book = book writer.sheets = dict((ws.title, ws) for ws in book.worksheets) data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2']) writer.save()
Explanation
- load_workbook opens the existing Excel file and assigns it to the book variable.
- ExcelWriter is initialized with the engine='openpyxl' parameter to use the openpyxl engine for writing.
- The writer.book attribute is set to the book variable, linking the writer to the existing workbook.
- writer.sheets is updated with a dictionary of all existing sheets, ensuring that the "Main" sheet is recognized and retained.
- Pandas' to_excel method fills in data for the "Main" sheet without affecting others.
- writer.save completes the operation, preserving both existing and new data.
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