Python Excel Automation
Practical Python tutorials for Excel automation and reporting workflows
Explore production-focused guides that turn recurring Excel reporting into maintainable, automated workflows — pandas, Polars and openpyxl for the data, xlsxwriter for the output, SQL, API and spreadsheet sources upstream, and scheduling, containers, delivery, testing and packaging around the whole job. Start by choosing the right library, translate the spreadsheet formulas you are replacing into pandas, and drive Excel itself when only Excel will do. Every file format, date and timezone problem you will meet is covered too, along with the errors that stop a job at six in the morning.
Quick snapshot
- Reading, writing, formulas, validation and large-file techniques in one place
- openpyxl, pandas, xlsxwriter, xlwings and Polars — compared, so you pick once
- SUMIF, COUNTIF, VLOOKUP and nested IFs translated into pandas, function by function
- Every format you will meet: .xlsx, .xlsm, legacy .xls, .xlsb, .ods and CSV
- The errors that stop a job at 06:00, decoded and fixed one by one
- Driving Excel itself with COM and xlwings, and knowing when not to
- SQL, API and Google Sheets sources in, formatted workbooks out, on a schedule
- Delivery by email, Graph, Teams, S3, SharePoint, Drive, Slack — or a download endpoint
- Docker, Airflow, testing and packaging so somebody else can run the job
Learn in pathways
Start with core Excel automation concepts, then move into data cleaning and reporting delivery.
Read dense technical guides
Each section is optimized for long-form writing, code blocks, tables, and deep internal cross-links.
Move faster in production
Patterns emphasize repeatable pipelines, reproducible output, and real reporting workflow concerns.
Browse by track
Start from a topic
Pick a track and drill down into focused guides and subtopics.
Learning path
Advanced Data Transformation and Cleaning for Excel Automation
Build production-grade Python pipelines that clean, validate, merge, and format Excel data with pandas and…
Explore topicLearning pathAutomating Reporting Workflows with Python and Excel
Build an end-to-end Python reporting pipeline: ingest data, transform it with pandas, generate a styled Excel…
Explore topicLearning pathFormatting and Charting Excel Reports with Python
Turn plain pandas output into branded, stakeholder-ready Excel reports: cell styling, number and date formats…
Explore topicLearning pathGetting Started with Python Excel Automation
Learn how to read, transform, and write Excel files with Python using pandas and openpyxl — the libraries, the…
Explore topicNewly added
Latest topics
The most recent additions to the catalogue, each with its own set of step-by-step guides.
New topic
Choosing a Python Excel Library
openpyxl, xlsxwriter, pandas, Polars or xlwings? Compare what each library can actually do — read, write, edit in place, drive…
Read the guidesNew topicExcel Formula Equivalents in pandas
Translate SUMIF, COUNTIF, VLOOKUP, INDEX MATCH, nested IFs and text functions into pandas — with the mask-select-aggregate pattern…
Read the guidesNew topicAutomating Excel with COM and pywin32
Drive a real copy of Excel from Python: attach with win32com, move ranges in one call, run macros and refresh queries, and quit…
Read the guidesNew topicReading Excel with Polars and Arrow
Read and write Excel with Polars and Arrow-backed engines: polars.read_excel, the calamine reader, lazy pipelines, Parquet…
Read the guidesStart here
Featured guides
Hand-picked walkthroughs, including the newest topics on choosing between the Python Excel libraries, translating spreadsheet formulas into pandas, and driving Excel itself with COM and pywin32.
- 01Choosing a Python Excel Library: openpyxl vs xlsxwriter vs pandasopenpyxl, xlsxwriter, pandas, Polars or xlwings? Compare what each library can actually do — read, write, edit in place…
- 02Excel Formula Equivalents in pandasTranslate SUMIF, COUNTIF, VLOOKUP, INDEX MATCH, nested IFs and text functions into pandas — with the…
- 03Reading Excel Files with PandasLoad Excel workbooks into pandas DataFrames: pick the engine, target sheets and columns, control dtypes, and read…
- 04Automating Excel with COM and pywin32Drive a real copy of Excel from Python: attach with win32com, move ranges in one call, run macros and refresh queries…
- 05Fix Common Python Excel ErrorsDecode the errors Python throws at Excel files: BadZipFile, InvalidFileException, engine errors, missing worksheets…
- 06Read Excel with Polars and ArrowRead and write Excel with Polars and Arrow-backed engines: polars.read_excel, the calamine reader, lazy pipelines…
- 07Serve Excel Downloads from Python AppsGenerate and return .xlsx from Flask, FastAPI and Django: in-memory workbooks, correct headers, streaming, background…
- 08Excel Dates in Python: Parsing, Serials and TimezonesHandle Excel dates correctly in Python: the serial-number model, parsing mixed date text with pandas, timezone-aware…
- 09Publish Excel Reports to S3, SharePoint and DriveDeliver generated Excel reports where people already look: S3, SharePoint and OneDrive, Google Drive, and network shares…
- 10Protect and Share Excel Workbooks from PythonControl what readers can change in a generated Excel report: sheet and workbook protection, locked cells, hidden sheets…
- 11Move Data Between Excel and SQL with PythonExcel as the interface, the database as the source of truth: query to workbook with SQLAlchemy, load a spreadsheet into…
- 12Build Excel Reports with xlsxwriter in PythonThe write-only engine that formats fastest: reusable format objects, column-level formatting, charts, conditional…