How to automate Excel spreadsheets with Python openpyxl
Sep 26, 2025 am 05:10 AMUse the openpyxl library to automate Excel operations. After installation, import the library, create or load workbooks, read and write data through cell coordinates or row and column indexes, apply fonts and fill styles to improve readability, and finally save the file, support dynamic naming to avoid overwriting, and is suitable for repetitive tasks such as report generation.
Automating Excel spreadsheets with Python using openpyxl is a practical way to handle relative tasks like formatting, data entry, report generation, and analysis. This library allows you to read from and write to Excel (.xlsx) files without needing Microsoft Excel installed. Here's how to get started and apply common automation techniques.
Install and Load openpyxl
Before working with Excel files, install the library using pip:
pip install openpyxlThen import it in your script:
from openpyxl import Workbook, load_workbookYou can create a new workbook or load an existing file:
- Create new: wb = Workbook()
- Load existing: wb = load_workbook('data.xlsx')
Read and Write Cell Data
Access worksheets and cells directly by name or index:
ws = wb['Sheet1']Read a cell value:
value = ws['A1'].valueWrite to a cell:
ws['A1'] = 'Hello World'You can also use numeric row and column indexing with cell(row, col) :
ws.cell(1, 2).value = 'Column B'This flexibility makes it easy to loop through rows and update values ??dynamically.
Apply Formatting and Styles
Enhance readingability by applying fonts, borders, and colors:
from openpyxl.styles import Font, PatternFillExample: Make text bold and set background color:
ws['A1'].font = Font(bold=True)ws['A1'].fill = PatternFill(start_color="FFFF00", end_color="FFFF00", fill_type="solid")
Use this for headers or highlighting key data automatically after processing.
Save Your Changes
After making updates, save the workbook:
wb.save('updated_file.xlsx')If you're generating reports, include timestamps in filenames to avoid overwriting:
from datetime import datetimewb.save(f'report_{datetime.now().strftime("%Y%m%d_%H%M")}.xlsx')
Basically just combine reading, modifying, and styling steps into a script that runs on demand or as part of a larger workflow. openpyxl handles most standard Excel operations cleanly and efficiently.
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