Topic area
Reading & writing workbooks
Getting data out of a workbook and back into one — every format, every layout, every sheet.
Topics in reading & writing workbooks
Each topic page gathers every guide, how-to, comparison and fix on its subject.
- Reading Excel filesread_excel, openpyxl and the options that decide what actually lands in your DataFrame.
- Writing Excel filesto_excel, ExcelWriter and appending to workbooks that already exist.
- Many sheets & many filesCombine a folder of workbooks, split one by value, copy and reorder sheets.
- File formats & conversion.xlsx, .xlsm, .xls, .xlsb, .ods, CSV, JSON and Parquet — reading each and converting between them.
- Messy spreadsheetsShifting headers, stacked tables, merged cells and subtotal rows in sheets people built by hand.
Reading Excel files
- GuideExtracting Data from Messy Excel Sheets
- GuideReading Excel with Polars and Arrow
- OverviewGetting Started with Python Excel Automation
- GuideReading Excel Files with Pandas
Writing Excel files
- GuideBuilding Excel Reports with xlsxwriter
- OverviewGetting Started with Python Excel Automation
- GuideUsing openpyxl for Excel File Manipulation
- GuideWriting DataFrames to Excel with Pandas
Many sheets & many files
- GuideWorking with Multiple Excel Sheets in Python
- How-toConsolidate Timesheets from Many Workbooks with Python
- How-toApply the Same Change to Every Sheet in a Workbook
- How-toCombine Multiple Excel Files into One in Python
File formats & conversion
- GuideHandling Excel File Formats and Conversions
- How-toConvert Excel Files to Parquet with Python
- How-toConvert Excel to CSV with Python
- ComparisonExcel vs CSV vs Parquet for Python Data Pipelines
Messy spreadsheets
- GuideExtracting Data from Messy Excel Sheets
- How-toCombine Sheets with Different Layouts into One Table
- How-toExtract Hyperlink URLs from Excel Cells with openpyxl
- How-toExtract Report Header Fields from an Excel Sheet with Python
Other areas